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Secondary User Power Control Aided Cooperative Spectrum Sensing
Bin SHEN, Zhiqiang WANG, Han QING
, doi: 10.11999/JEIT171232
[Abstract](24) [FullText HTML](16) [PDF 1413KB](6)
In conventional cooperative spectrum sensing, the spectrum sensing model is usually simplified as a single-stage channel environment where the Secondary Users (SUs) collect their spectrum data and report to the Fusion Center (FC) with the same transmit power. This hampers the FC from efficiently exploiting the space diversity gain beneath the data of different users. In order to solve this problem and control the user transmit power in reporting their data, three Optimal Power Control (OPC) schemes are proposed. When the Channel Statistic (CS) of the sensing channel and the reporting channel are perfectly known at the FC, a CS Aided Optimal Power Control (CSA-OPC) scheme is derived in closed-form, whereas when the CS is practically unavailable, Principal EigenVector aided OPC (PEV-OPC) and Blindly Weighted Multiple-EigenVector aided OPC (BWMEV-OPC) schemes are developed. Theoretical analysis and computer simulation verify that the propose OPC schemes greatly ameliorate the spectrum performance, compared to the non-OPC aided cooperative spectrum sensing schemes.
Noise Suppression Algorithm for Ocean Magnetic Anomaly Detection
Chunjiao FEI, Qunying ZHANG, Peilin WU, Guangyou FANG, Wanhua ZHU, Xin XU
, doi: 10.11999/JEIT180026
[Abstract](23) [FullText HTML](18) [PDF 2814KB](2)
Marine magnetic anomaly detection is one of the basic means of marine scientific observation, exploration of undersea resources, national defense and security. However, the complexity of the magnetic field noise increases the difficulty of the magnetic detection. It is of great significance to study various magnetic field noise mechanisms and suppression methods for the improvement of measurement accuracy. In this paper, the wave magnetic field model under general and infinite depth conditions is used to estimate the noise induced by sea waves respectively. The wave and geomagnetic noise in the magnetic anomaly signal is filtered out by the combination of spectral subtraction and wavelet. In order to verify the validity of the algorithm, the ocean magnetic field in a sea area of South China Sea in August 2015 is observed. The results show that this method can filter out most of the wave and geomagnetic field noise. The wave distribution in the frequency range of 0.4~0.8 Hz is obviously reduced, the waveform in the time domain is greatly improved, the magnetic anomaly signal of the target is highlighted. Signal to noise ratio can be increased by nearly 11 dB. The proposed method has the advantages of low computational complexity, strong real-time performance and easy implementation, which can provide an effective measure for noise suppression of marine magnetic anomaly detection.
Novel Method for Outlier Nodes Detection and Localization in Wireless Sensor Networks
Junzheng JIANG, Jie YANG, Shan OUYANG
, doi: 10.11999/JEIT171207
[Abstract](41) [FullText HTML](13) [PDF 1278KB](5)
The outlier nodes detection and localization in Wireless Sensor Networks (WSNs) is a crucial step in ensuring the accuracy and reliability of network data acquisition. Based on the theory of graph signal processing, a novel algorithm is presented for outlier detection and localization in WSNs. The new algorithm first builds the graph signal model of the network, then detect the location of the outlier based on the method of vertex-domain and graph frequency-domain joint analysis. Specifically speaking, the first step of algorithm is extracting the high-frequency component of the signal using a high-pass graph filter. In the second step, the network is decomposed into a set of sub-graphs, and then the specific frequency components of the output signal in sub-graphs are filtered out. The third step is to locate the suspected outlier center-nodes of sub-graphs based on the threshold of the filtered sub-graphs signal. Finally, the outlier nodes in the network are detected and located by comparing the set of nodes of each sub-graph with the set of suspected outlier nodes. Experimental results show that compared with the existing outlier detection methods in networks, the proposed method not only has higher probability of outlier detection, but also has a higher positioning rate of outlier nodes.
Research on the Construction of Plateaued Functions
Tianfeng SUN, Bin HU, Yang YANG
, doi: 10.11999/JEIT170965
[Abstract](4) [FullText HTML](3) [PDF 0KB](0)
Plateaued functions play a significant role in cryptography, coding theory and so on. In this paper, a new primary construction of plateaued function is given. Some cryptographic properties of the constructed plateaued functions are studied. It is shown that the existing primary constructions of plateaued function can be reduced to the proposed construction.
q -affine Projection Algorithm and Its Steady-state Mean Square Convergence Analysis
Shiyuan WANG, Chunfen SHI, Yunxiang JIANG, Wenyue WANG, Guobing QIAN
, doi: 10.11999/JEIT171125
[Abstract](84) [FullText HTML](71) [PDF 937KB](25)
The q-gradient is a generalized gradient based on the q-derivative concept. To improve the filtering performance of the Affine Projection Algorithm (APA), the q-gradient is applied to APA based on the minimum of the recent mean square errors, generating a novel q-Affine Projection Algorithm (q-APA). The q-APA with appropriate setting of q achieves desirable filtering performance in the presence of Gaussian noises. A sufficient condition for guaranteeing convergence of the proposed q-APA is also presented, and its steady-state Excess Mean Square Error (EMSE) of q-APA is obtained theoretically to evaluate the filtering performance. In addition, the Variable q-APA (V-q-APA) is developed to improve further the filtering performance. Simulations in the context of system identification demonstrate the superior filtering performance of the proposed algorithms compared with APA and Variable q-Least Mean Square (V-q-LMS) algorithm in the presence of Gaussian noise.
Artificial Noise Aided Secure Transmission in Dense Heterogeneous Cellular Networks with Imperfect Channel State Information
Yunjia XU, Kaizhi HUANG, Jun LI, Yajun CHEN
, doi: 10.11999/JEIT180003
[Abstract](50) [FullText HTML](16) [PDF 1313KB](2)
To ensure secure transmission in dense heterogeneous cellular networks with imperfect Channel State Information (CSI), the influence of Artificial Noise (AN) on secure and reliable communication is analyzed, and a power split factor optimization model is presented to obtain the optimal value under different channel estimation accuracy. First, the connection outage probability and secrecy outage probability are deduced by considering the influence of channel estimation error on signal transmission and AN leakage. Then, a power split factor optimization model is presented, which maximizes the secrecy throughput subject to the security and reliability requirements. A K-dimensional search method is employed to solve the optimal power split factor of each tier. Finally, the numerical results verify that the AN transmission scheme with optimal power split factor can increase secrecy throughput by about 15%.
Gain and Phase Calibration Algorithm of Near-field Source Based on Instrumental Sensors
Mengyu NI, Hui CHEN, Song XIAO, Liuliu NI, Jiajia ZHANG
, doi: 10.11999/JEIT180032
[Abstract](16) [FullText HTML](8) [PDF 1779KB](0)
In order to solve the problem of near-field source localization and array gain-phase error calibration, a method of gain-phase error calibration is proposed based on uniform array symmetry. The distance parameter is separated by reconstructing the virtual array, and then the decoupling between azimuth and error is realized by transforming the steering vector of the virtual array. Through the transformation of the real array steering vector, the decoupling between the distance and the gain-phase error is realized, and the cascade estimation of the azimuth and distance of the near-field source and the gain-phase error coefficient of the array is achieved. The simulation results show that compared with the exist algorithms, the proposed algorithm has less computational complexity, more accurate azimuth and distance parameters estimation, and higher accuracy of gain and phase error calibration.
Polarimetric SAR Coherent Change Detection Method Based on Volume Scattering Constraint
Guangyu JI, Xingdong LIANG, Yongwei DONG, Yanlei LI
, doi: 10.11999/JEIT180035
[Abstract](43) [FullText HTML](37) [PDF 9276KB](10)
Coherent Change Detection (CCD) detects change areas in the scene using its decorrelation, yet vegetation areas with volume scattering and low signal-noise ratio areas in the scene also appear as low coherence, which causes interference to change areas to be detected. A polarimetric SAR CCD method is proposed. Firstly, the polarimetric coherence between two SAR images before and after changing is employed to set up weighted trace coherence statistics. Secondly, the polarimetric coherence between channels of each SAR image is employed to set up volume scattering constraint by establishing GEV mixture distribution model and solving parameters of each part using improved EM algorithm. Lastly, constraint of scattering power change is combined to set up the final polarimetric CCD test statistics. Using this method, the interference could be eliminated without influence of detect performance. The method is validated by two L-band full-polarimetric SAR images before and after changing. Results and index parameters demonstrate the correctness and validity of the proposed method.
User Identification Across Social Networks Based on User Trajectory
Hongchang CHEN, Qian XU, Ruiyang HUANG, Xiaotao CHENG, Zheng WU
, doi: 10.11999/JEIT180130
[Abstract](45) [FullText HTML](26) [PDF 631KB](11)
The performance of trajectory based user identification is poor since the existing methods ignore the order feature of location sequence. To solve this problem, a Cross Domain Trajectory matching algorithm based on Paragraph2vec (CDTraj2vec) is proposed. Firstly, the user trajectory is transformed to the grid representation which is easy to handle. And the PV-DM model in the Paragraph2vec algorithm is utilized for extracting order feature of location sequence in trajectory. Then the original user trajectories are divided by a certain time size and distance scale to construct a training sample suitable for training PV-DM model. The PV-DM model is trained by different types of training samples, and the vector representation of the user trajectories is obtained. Finally, the matching of the trajectory is determined by the user trajectory vector. Experimental results on BrightKite shows that the F-measure is improved by 2%~4% compared with the existing frequency based and distance based algorithm. The proposed algorithm can effectively extract the order feature of location sequence, and realize the trajectory based user identification across social networks.
Integrated Enhancement Algorithm for Hazy Image Using Transmittance as Weighting Factor
Julang JIANG, Wei SUN, Zhendong WANG, Zhu ZHU, Jiangyun ZHENG
, doi: 10.11999/JEIT171032
[Abstract](32) [FullText HTML](18) [PDF 2738KB](2)
Hazy image enhancement has important practical significance. Since the existing haze removal algorithms have disadvantages in improving the global contrast of images, a novel hazy image enhancement algorithm is presented by integrating advantages of haze removal and histogram equalization. Firstly, the hazy image is processed respectively using guided filtering-based dark channel prior algorithm and HSV space-based histogram equalization algorithm. Then, the output image is obtained by fusing the above two results using weighting factor which is constructed by the revised transmittance map. Simulation results show that the algorithm has higher standard deviation, average gradient and information entropy than the present hazy removal algorithm, and shows better result of global and local contrast. The running time of the algorithm mainly depends on the process of haze removal, which can meet the real-time requirements for normal size image.
Non-Invasive Wireless and Passive MEMS Intraocular Pressure Sensor
Junbo WANG, Chaochao HE, Deyong CHEN, Jian CHEN, Qiuxu WEI
, doi: 10.11999/JEIT180045
[Abstract](24) [FullText HTML](9) [PDF 2434KB](0)
Continuous monitoring of IntraOcular Pressure (IOP) plays an important role in the diagnosis and treatment of the glaucoma. Existing IOP sensors have some problems, such as low sensitivities, high central resonant frequencies and difficult fabrication. In order to solve the aforementioned problems, this paper presents a wireless, passive and non-invasive IOP sensor based on MEMS technology. The sensor contains five stacked layers, where Parylene, copper and PDMS are adopted as the functional materials within two flexible substrate layers, two electrode layers, and a dielectric layer, respectively. The electrode layers and the dielectric layer consist of two inductors and two capacitors to form a resonant circuit in C-L-C-L series. In the term of fabrication, a MEMS planar process followed by thermally shaping is proposed to fit curved surfaces of the eyeballs, and then this design scheme can effectively solve such issues as the difficulty in making the sensor and so on. Experimental results show that the central resonant frequency is decreased to 40 MHz, relative sensitivity is quantified as 1028.57 ppm/kPa, and resolution reached up to 50 Pa (0.375 mmHg). This study can be used for long-term, continuous monitoring of IOP.
Study on Electron Emission Phenomenon of the Surface Micro Area of Coated Impregnated Dispenser Cathode
Shengyi YIN, Feng REN, Zhipeng LU, Yongqing ZHANG, Shenjin ZHANG, Feng YANG, Dong WEI, Jiao HAN, Yang LI
, doi: 10.11999/JEIT171000
[Abstract](29) [FullText HTML](7) [PDF 1816KB](0)
The impact on impregnated cathode electronic emission, when it is coated by films, is an important studied content in the field of thermionic cathode. A cathode sample is evenly split by impregnated dispenser cathode and coated impregnated dispenser cathode. The sample is activated at 1150 ℃ in the Deep UltraViolet laser Photo- and Thermal- Emission Electron Microscope system (DUV-PEEM/TEEM) for 2 hours. In this system, the micro- electron emission phenomenon of two cathode and its changes with temperature are compared and studied directly. The results show that the electronic emission of both impregnated cathode and coated impregnated cathode are mainly located at the pores and the edge of the adjacent particles; Along with the rise of cathode's temperature, the cathode emission without coating anything is still mainly focused on the pores and nearby narrow regions on cathode surface, that the emission area changed a little. However, for the coated impregnated dispenser cathode, the effective emission area is extended from the pores and its edge to the area far away from the pores. These results for the first time give the electron emission characteristics for impregnated cathode coated with film, which have certain reference value to understand the emission mechanism of this cathode.
Single Base Station Localization Algorithm Based on B-LM Ring of Scattering Model Using NLOS Information
Zengshan TIAN, Yueyue SHU, Mu ZHOU, Yong LI, Ze LI
, doi: 10.11999/JEIT171222
[Abstract](9) [FullText HTML](2) [PDF 1996KB](0)
Considering the requirements of time and data synchronization in multi-BS (Base Station) positioning in the current outdoor cellular network and the problem of signals’ detectability in area without service BS due to NLOS (Non-Line-Of-Sight) environment, a single base station localization algorithm based on B-LM (Broyden Fletcher Goldfarb Shanno-Levenberg Marquard) ring of scattering model using NLOS information is proposed. Firstly, the localization objective equation is constructed according to the geometric positions of the scatterers, the target, the base station and the NLOS multipath information. Then, the localization equation is transformed into the least square optimization problem. Finally, the B-LM algorithm based on Hessian matrix modification methodology in LM algorithm and the construction of second order partial derivative in quasi-Newton algorithm is proposed, which ensures the localization algorithm converges to the optimal solutions to obtain the target’s location. The simulation results show that the proposed single base station localization algorithm can achieve a high positioning accuracy in the NLOS environment for macrocell.
A Non-stationary 3D Spatial Channel Model Based on Stochastic Scattering Cluster
Wei ZHANG, Jingjing DUAN, Yansong WANG
, doi: 10.11999/JEIT170929
[Abstract](9) [FullText HTML](2) [PDF 1756KB](0)
To describe the near field effect and the non-stationary characteristic of the Massive MIMO channel, a non-stationary 3D spatial channel model based on stochastic scattering clusters for Massive MIMO systems is proposed. The parabolic wave instead of the spherical wave is used to model the near field effect, and the channel capacity of the model is analyzed under parabolic wavefront condition. For non-stationary properties of massive MIMO channel, the effective scattering clusters set of transmitting and receiving antenna elements is determined based on the effective probability of scattering clusters, and the stochastic evolution of scattering clusters along the antenna array axis is modeled to describe properly the appearance and disappearance of scattering clusters. Simulation results demonstrate that parabolic wavefront and the stochastic evolution of effective scattering clusters are good candidates to model Massive MIMO channel characteristics.
Multipath Clutter Rejection Approach Based on Carrier Domain Adaptive Iterative Filter in Passive Bistatic Radar
Zhixin ZHAO, Xinhua ZHOU, Sheng HONG, Tao WENG, Yuhao WANG
, doi: 10.11999/JEIT180097
[Abstract](35) [FullText HTML](10) [PDF 1638KB](1)
In passive bistatic radar systems, there exists the zero and non-zero Doppler shift multipath clutter in the surveillance channel. The multipath clutter affects the target detection. Temporal adaptive iterative filter such as Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) are often used to reject multipath clutter in passive bistatic radar, but these methods are only applicable to reject zero Doppler shift multipath clutter. To solve the problem of zero and non-zero Doppler shift multipath clutter, combined with the orthogonal frequency division multiplexing waveform features of digital broadcasting television signals, a clutter rejection algorithm is proposed based on carrier domain adaptive iterative filter. The algorithm utilizes the correlation of multipath clutter with the same Doppler shift at the same carrier frequency in subcarrier domain to reject the zero and non-zero Doppler shift multipath clutter. Simulation and experiment data processing results show the superiority of the proposed algorithm.
Resources Balancing Algorithm Based on the Time-frequency Fragment Awareness for Virtual Optical Network Mapping
Huanlin LIU, Cuilian XIONG, Yong CHEN, Min XIANG, Yue MA
, doi: 10.11999/JEIT171208
[Abstract](46) [FullText HTML](15) [PDF 1842KB](2)
In order to address the problems of the high bandwidth blocking probability and imbalance resources consumption in physical network during virtual optical network mapping, Fragmentation-Aware based on time and spectrum domain of Virtual Network Mapping (FA-VNM) algorithm is proposed. In the FA-VNM algorithm, the fragments problem in the time domain and the spectrum domain is considered. Fragment formula jointly considering the time fragment and spectrum fragment is devised to minimize the spectrum fragments. Further, in order to balance the network resources consumption, based on the FA-VNM, Load Balancing based on degree of Virtual Network Mapping (LB-VNM) algorithm is proposed. In the stage of node mapping, physical node average resource carrying capacity is introduced and the physical node with larger average resources carrying capacity is mapped first. In order to balance the resource consumption in physical path, weight value of physical path is calculated in the stage of link mapping. Then, according to the weight value of each physical path, virtual links are mapped to achieve the purpose of load balancing for reduce the blocking rate. Simulation results show that the algorithms can effectively reduce the blocking rate and improve the resources utilization.
A Suppression Algorithm of Blanket-distance Deception Compound Jamming based on Joint Signal-data Processing
Guohong WANG, Jie BAI, Dianxing SUN, Xiangyu ZHANG
, doi: 10.11999/JEIT170759
[Abstract](9) [FullText HTML](1) [PDF 2160KB](0)
Considering at the problem that the suppression effect of single signal processing or data processing is poor on blanket-deception compound jamming, a suppression algorithm of blanket-distance deception compound jamming based on joint signal-data processing is proposed. Firstly, the Fractional Fourier Transform (FRFT) domain narrowband filtering and LFM signal reconstruction algorithm are used to suppress the suppression of the signal layer and reduce the leakage probability of the real target. Then, the target tracks and the deception tracks are rejected by using the M/N logic method. Finally, according to the different characteristics of the angle variance between the false targets and the true targets, the false targets are eliminated by the \begin{document}${\chi ^2}$\end{document} test and the clustering algorithm. The simulation results verify the good effect of the algorithm proposed in this paper.
Neighbor Discovery Mechanism for Underwater Acoustic Communication Networks Based on Directional Transmission and Reception
Jianmin YANG, Gang QIAO, Donghu NIE, Lu MA
, doi: 10.11999/JEIT180108
[Abstract](59) [FullText HTML](45) [PDF 1632KB](9)
Considering the difficulty of neighbor discovery in underwater acoustic communication networks, a neighbor discovery mechanism is presented based on directional transmission and reception. In this mechanism, the nodes only send and receive signals directionally, which can avoid the hidden terminal problem caused by asymmetric gain and increase the network coverage. Time is divided into neighbor discovery time slot and listening & reply time slot. In neighbor discovery time slot, the node sends the HELLO signal, and then waits to receive the REPLY signal sent by its neighbor node. In listening & reply time slot, the node listens the channel for the HELLO signal sent by the source node, then replies REPLY signal to the source node. The node can discover its neighbor through HELLO/REPLY two-way handshake based on competition and direct & indirect discovery, which can overcome the " deaf” nodes problem and improve the efficiency of neighbor discovery. Compared with the randomized two-way neighbor discovery mechanism, simulation tests show that the proposed mechanism has the shorter average discovery latency and the higher average discovery ratio in various network density and number of antenna sectors.
Timing Synchronization Method for Continuous Phase Frequency Shift Keying Signal Based on Multi-symbol Detection
Tian LIU, Song MA, Tian YUAN, Shihai SHAO
, doi: 10.11999/JEIT180060
[Abstract](22) [FullText HTML](14) [PDF 1972KB](2)
Continuous Phase Frequency Shift Keying (CPFSK) is widely adopted as a standard by the telemetry community. The Multi-Symbol Detection (MSD) technique can increase channel gain for the CPFSK telemetry system. Therefore, the timing synchronization method for CPFSK signal needs to adapt to the scenario with lower SNR. According to existing timing synchronization methods’ poor performance in low SNR, a novel timing synchronization method for CPFSK signal based on MSD is proposed, which is suitable to variable rate. The simulation results show that, when Eb/N0 is 0 dB and symbol rate is 2 Mbps, the proposed method achieves 2 dB more channel gain than the single symbol likelihood decision method, and has similar performance to the early-late gate code synchronization method with reduced hardware resource by 60%. Finally, the validity of the numerical simulation and resource evaluation is verified by principle prototype realization.
Low Complexity Iterative Parallel Interference Cancellation Detection Algorithms for Massive MIMO Systems
Bin SHEN, Shufeng ZHAO, Chun JIN
, doi: 10.11999/JEIT180111
[Abstract](12) [FullText HTML](10) [PDF 1581KB](3)
Based on interference cancellation method, a low complexity Iterative Parallel Interference Cancellation (IPIC) algorithm is proposed for the uplink of massive MIMO systems. The proposed algorithm avoids the high complexity matrix inversion required by the linear detection algorithm, and hence the complexity is maintained only at \begin{document}$({\cal O}({K^2}))$\end{document} . Meanwhile, the noise prediction mechanism is introduced and the noise-prediction aided iterative parallel interference cancellation algorithm is proposed to improve further the detection performance. Considering the residual inter-antenna interference, a low-complexity soft output signal detection algorithm is proposed as well. The simulation results show that the complexity of all the proposed signal detection methods are better than that of the MMSE detection algorithm. With only a small number of iterations, the proposed algorithm achieves its performance quite close to or even surpassing that of the MMSE algorithm.
Research on Characteristics and Suppression Methods of Side Peaks of Passive Radar Based on LTE Signal
Xiaode LÜ, Hanliang ZHANG, Jingmao YANG, Qi YUE
, doi: 10.11999/JEIT180019
[Abstract](14) [FullText HTML](11) [PDF 2739KB](1)
For the passive radar based on Long Term Evolution (LTE) signal, firstly, the ambiguity function are analyzed, and the producing mechanism of different side peaks are explained. Then, a series of corresponding suppression algorithms are proposed for two types of side peaks degrading detection performance: For the side peaks caused by the cyclic prefix, a fast ambiguity algorithm based on non-continuous chunking of data is proposed; For the side peaks caused by the non-continuous spectrum, the suppression algorithm of bandwidth synthesis and frequency domain windowed is proposed. Finally, the thumbtack ambiguity function of the LTE signal is obtained through integrated processing of two suppression algorithms. The work of this paper provides a new method for the side peaks suppression of the passive radar based on the LTE signal.
Matrix Pencil Method Based Processing Approach for Spaceborne MEB SAR with Digital Beamforming in Elevation
Kai YE, Weidong YU, Wei WANG
, doi: 10.11999/JEIT180076
[Abstract](2) [FullText HTML](1) [PDF 2001KB](0)
Digital BeamForming (DBF) in elevation plays a crucial role for spaceborne Multiple Elevation Beam (MEB) SAR realizing the High-Resolution Wide-Swath (HRWS) imaging mode. However, due to the influence of satellite attitude error, the deviation of the DBF receiving beam direction always arises in such system. This leads to ghost targets appearing in the SAR image, when mapping the scenes (such as the seaport areas) with strong scatterers. To address the problem, a matrix pencil method based DBF processing approach in elevation is presented. Firstly, according to the given threshold, the peak position of the strong scatterer is found from the range-compressed signals. Then, the direction of arrival angle of the strong scatterer is estimated using the matrix pencil method. Finally, based on the imaging geometry model, the DBF weighting vector is adjusted to ensure the receiving beam to precisely point to the signal sources. Thereby, the interferences of ghost targets in SAR image can be eliminated effectively. The theoretical analysis is derived in detail, then it is validated by simulation experiments.
Clutter Suppression Method for Short Range Slow Moving Target Detection
Lin ZHENG, Weiwei YAO, Chao YANG, Hongbing QIU
, doi: 10.11999/JEIT180031
[Abstract](18) [FullText HTML](11) [PDF 1772KB](3)
This paper proposes a method of clutter suppression based on phase encoding and subspace projection for close slow-moving target detection in strong clutter environment. In the framework, the periodic detection signal is modulated with phase encoding, and the clutter is whitened through echo decoding of the slow-time dimension to reduce the correlation between clutter and target echo. Furthermore interference subspace is constructed on the basis of the autocorrelation differences between whitened clutter and useful signal components. The receiving signal is projected to the signal subspace orthogonal to the clutter subspace for clutter suppression. Since the construction of clutter space does not need to assume the clutter model, it avoids the problem of mismatch between the model hypothesis and the actual environment. Simulation results and real data processing results show that this method has better performance than conventional methods under low signal-to-clutter ratio.
Research on Resource Allocation Algorithm for D2D Communications Underlaying LTE-A Networks
Zhihong QIAN, Shuangye YAN, Chunsheng TIAN, Xin WANG
, doi: 10.11999/JEIT180043
[Abstract](13) [FullText HTML](6) [PDF 1313KB](0)
Uplink resource allocation problem in Device-to-Device (D2D) communications underlaying LTE-A networks is analyzed. First, the problem is modeled as a Mixed Integer NonLinear Programming (MINLP). Then the algorithm calculates each waiting user’s identity list in accordance with the preference for channels to form coalitions. On the premise of guaranteeing the Quality of Service (QoS) of users in the system, the suitable resource and reuse partner are assigned to each user through Maximum Weighted Bipartite Matching (MWBM). The simulation results show that this algorithm can break the constraint that D2D pairs can only stay on dedicated or reused mode when they are on data transmission, and expand the range of available resource for D2D users, which increases effectively the system sum-rate compared with the existing algorithm.
Calculation of Electromagnetic Propagation Characteristics over Rough Sea Surface Based on Double-layer Model
Mengda CUI, Hao CHA, Bin TIAN, Qun WANG
, doi: 10.11999/JEIT171020
[Abstract](12) [FullText HTML](7) [PDF 897KB](0)
A double-layer model is proposed to reduce the calculation amounts of the Linear Ship Map (LSM) model. The proposed model can be used for rapid and accurate calculation of the electromagnetic propagation characteristics in the complicated atmospheric environment over the sea. In the proposed model, the calculation regions are divided into the upper-layer and the lower-layer. The upper-layer is calculated by the Wide angle Parabolic Equation (WPE) model and the lower-layer is calculated by the LSM model. Through reducing the calculation height and optimizing the step length, the proposed model can be exact and rapid. By simulation, the proposed model is compared with LSM model in the smooth and the rough sea surface conditions. The results show that the proposed model can decrease the calculation time by 1/10 in the rough sea surface condition.
Modified MUSIC Algorithm for Multiple Measurement Vector Models
Yun LIN, Qiang HU
, doi: 10.11999/JEIT180001
[Abstract](23) [FullText HTML](7) [PDF 1157KB](0)
The Compressed Sensing (CS) Multiple Measurement Vector (MMV) model is used to solve multiple snapshots problem with the same sparse structure. MUltiple SIgnal Classification (MUSIC) is a common method in traditional array signal processing applications. However, when the number of snapshots is below sparsity performance will be dramatically deteriorated. Kim et al. derive a modified MUSIC spectral method and propose a Compressed Sensing MUSIC method (CS-MUSIC) combining the compression reconstruction method and the MUSIC algorithm, which can effectively overcome the problem of insufficient snapshot number. In this paper, Kim et al.’s conclusion is extended to the general case, and a Modified MUSIC (MMUSIC) algorithm is proposed based on the traditional MUSIC method and the CS-MUSIC method. The simulation results show that the proposed algorithm can effectively overcome the shortage of snapshots and has a higher reconstruction probability than the CS-MUSIC algorithm and the compressed sensing greedy algorithm.
V2X Task Offloading Scheme Based on Mobile Edge Computing
Haibo Zhang, Qiuji Luan, Jiang Zhu, Xiaofan He
, doi: 10.11999/JEIT180027
[Abstract](3) [FullText HTML](1) [PDF 1427KB](0)
Mobile Edge Computing (MEC) draws much attention in the next generation of mobile networks with high bandwidth and low latency by enabling the IT and cloud computation capacity at the Radio Access Network (RAN). Matching problem between requesting nodes and servicing nodes is studied when a vehicle wants to offload tasks, a MEC-based offloading framework in vehicular networks is proposed, Vehicle can either offload task to MEC sever as V2I link or neighboring vehicle as V2V link. Taking into account the limited and heterogeneous resources, and the diversity of tasks, offloading framework is established as combination auction model, and a multi-round sequential combination auction mechanism is proposed, which consists of Analytic Hierarchy Process (AHP) ranking, task bidding and winners decision. Simulation results show that the proposed mechanism can maximize the efficiency of service nodes while increasing the efficiency of requesting vehicles under the constraints of the delay and the capacity.
Non-orthogonal-Code Index Modulation
Lijia GE, Zhilin JIANG, Sheng FENG, Qin YANG
, doi: 10.11999/JEIT180023
[Abstract](2) [FullText HTML](2) [PDF 1958KB](0)
To deal with the problem that the bit error rate reduces obviously when the Code Index Modulation (CIM) is used to improve spectrum utilization, a novel Non-orthogonal-Code Index Modulation (N-CIM) is proposed. The bit stream of the transmitter is divided into mapping block of Pseudo Noise (PN) code and informational block of modulation, which are mapped into the index of the PN code and modulation symbol respectively. The real part and imaginary part of the modulation symbol are spread by selecting the identical activate PN code. Simulation and analysis results show that N-CIM outperforms CIM by about 2~3 dB in additive white Gaussian noise channel when the bit error rate is 10–5, and N-CIM outperforms CIM by about 2 dB in Rayleigh fading channel when the bit error rate is 10–2 at the same spectral efficiency.
Robust Capon Beamforming for Towed Array Sonar During Maneuvering
Liankun BO, Xiaoyong ZHANG, Jinyu XIONG
, doi: 10.11999/JEIT180022
[Abstract](20) [FullText HTML](6) [PDF 1760KB](0)
The robust beamformer suffers performance degradation due to the distortion of towed array shape caused by the maneuverings of tow platform. To address this problem, a low complexity robust Capon beamforming method is proposed based on time-varying array focusing and dimension reduction. First, the array shape is estimated sequentially using the array heading data based on Water-Pulley model. The Sample Covariance Matrix (SCM) at each recording time is focused to a reference array model via the STeered Covariance Matrix (STCM) technique to eliminate the array model error. Then, the reducing transform matrix is formed based on the conjugate gradient direction vectors of the focused SCM. The reduced-dimension Capon beamformer is finally derived to calculate the spatial spectrum. The results of the simulations show that, the proposed method can improve the Signal-to-Interference-plus-Noise Ratio (SINR) of the beamforming during the maneuvering of towed array. The results of sea-trial data processing show that the proposed method can improve the output Signal-to-Noise Ratio (SNR) of the target, as well as the performance of detecting weak targets and solving the left-right ambiguity during maneuvering.
Hyperspectral Image Compression Based on Adaptive Band Clustering Principal Component Analysis and Back Propagation Neural Network
Shanxue CHEN, Yanqi ZHANG
, doi: 10.11999/JEIT180055
[Abstract](2) [FullText HTML](1) [PDF 915KB](0)
Hyperspectral remote sensing images have a wealth of spectral information and a huge universe of data. In order to utilize effectively hyperspectral image data and promote the development of hyperspectral remote sensing technology, a hyperspectral image compression algorithm based on adaptive band clustering Principal Component Analysis (PCA) and Back Propagation (BP) neural network is proposed. Affinity Propagation (AP) clustering algorithm for adaptive band clustering is used, and PCA is performed on the each band group respectively after clustering. Finally, all principal components are encoded and compressed by BP neural network. The innovation point lies in BP neural network compressed image during the training step, the error of backpropagation is to compare difference between the original image and the output image, and then adjust the weight and threshold of each layer in the reverse direction. Band clustering of hyperspectral images can not only effectively utilize the spectral correlation and improve the compression performance, but also reduce the computational complexity of PCA. Experimental results investigate that the proposed algorithm achieve a better performance on Signal-to-Noise Ratio (SNR) and spectral angle than other algorithm under the same compression ratio.
Research of Physiological Monitoring System Based on Optical Fiber Sensor
Rongjian ZHAO, Minfang TANG, Xianxiang CHEN, Lidong DU, Hualin ZENG, Zhan ZHAO, Zhen FANG
, doi: 10.11999/JEIT170894
[Abstract](16) [FullText HTML](5) [PDF 2537KB](2)
Conventionally, the physiological monitoring system obtains singnal by electrode or bandage which is connected with skins and has disadvantages such as: uncomfortable and bad compliance to users. In order to overcome those problems, a new physiological monitoring system, which is based on the principle that micro bend of optical-fiber induced by weak movement of physiology can change the light intensity to get BallistoCardioGram (BCG) signal, is developed. In such system, the respiration rate, heart rate and body movement are obtained by self-adaption detecting the tiny variation of light intensity. In order to protect fiber and enhance the stability and reliability of system, the fiber is embedded into mattress or cushion with a sandwich structure. Simultaneously, it makes the system have high sensitivity that the fiber is uniformly routed with serpentine-curve shape in the middle of mattress or cushion. It is illustrated by the measurement in several hospitals that the mean error of heart rate is –0.26±2.80 times/min within 95% the confidence interval (±1.96SD) with a correlation 0.9984 to the standard values. It is exhibited as well that the mean error respiration rate is 0.41±1.49 times/min within 95% the confidence interval (±1.96SD) with a correlation 0.9971 to the standard values. It is suggested that the developed system can be senselessly used under zero load and is promised in future.
False Moving Scene Jamming Method Based on Double Jammers and Magnitude Modulation Against SAR-GMTI
Xin CHANG, Chunxi DONG, Zhengzhao TANG, Yangyang DONG, Mingming LIU
, doi: 10.11999/JEIT171202
[Abstract](35) [FullText HTML](11) [PDF 1626KB](2)
To control the initial azimuth position and the magnitude of the false moving scene, a false moving scene jamming method against Synthetic Aperture Radar-Ground Moving Target Indication (SAR-GMTI) is proposed based on double jammers and magnitude modulation. The identical false scenes can be generated in the desired position by the two jammers using delay and shift-frequency modulation. To control the initial azimuth position of the false moving scene, the magnitude ratio of the double scenes are set by controlling the phase of each false target which is generated after two false scenes are superimposed. Theoretical analysis shows that the false moving scene can be generated with the initial azimuth position and magnitude controllable. Next, the jamming effects and influencing factors are analyzed, and the application model of interference algorithm is established. Subsequently, the setting methods of the imaging position, the initial azimuth position and the magnitude compensation coefficient are presented. The jamming effect of the distance between the two jammers in azimuth is also analyzed. Finally, the validity of the proposed method is verified by simulation experiences.
Micro-motion and Geometric Parameters Estimation of Wide-band Radar Cone-shaped Targets Based on Phase-derived Range
Jiaqi WEI, Lei ZHANG, Hongwei LIU, Yejian ZHOU
, doi: 10.11999/JEIT171233
[Abstract](55) [FullText HTML](12) [PDF 1583KB](2)
The traditional method used to extract micro-motion is based on the envelope information of the wideband echo range profile, the estimation accuracy of the traditional method is unsatisfactory. To deal with this problem, a new method for parameter estimation of micro-motion feature is proposed, which is implemented by combining envelope information and phase information of the wideband echo range profile. Firstly, the Keystone transform is performed to each segment obtained by segmenting the envelope of the echo range profile to estimate micro-motion coarsely. Then, the echo phase information is extracted according to the coarse estimation results. The accurate micro-motion curve of each scattering point can be obtained by the principle of phase-derived range. Finally, the estimation of the micro-motion and geometric parameters of the precession target is completed by utilizing the extracted micro-motion curve. Compared with the traditional method, the proposed algorithm can improve the precision of parameter estimation effectively. The effectiveness and stability of the proposed algorithm is verified by simulation experiments.
The Structure of (k,l)-recursive Maximal Planar Graph
Xiang’en CHEN, Ting LI
, doi: 10.11999/JEIT171021
[Abstract](75) [FullText HTML](5) [PDF 2062KB](2)
For a maximal planar graph G, the operation of extending 3-wheel is a process from G to Gv, where v is a new vertex embedded in some triangular face xyz of G and Gv is a graph of order |V(G)|+1 obtained from G by connecting v to each one of x, y, z with one edge. A recursive maximal planar graph is a maximal planar graph obtained from K4 by extending 3-wheel continuously. A (k,l)-recursive maximal planar graph is a recursive maximal planar graph with exactly k vertices of degree 3 so that the distance between arbitrary two vertices of degree k is l. The existence of (k,l)-recursive maximal planar graph is discussed and the structures of (3,2)-as well as (2,3)-recursive maximal planar graphs are described.
Maximum Eigenvalue Based Radar Signal Detection Method for K Distribution Sea Clutter Environment
Wenjing ZHAO, Chang LIU, Wenlong LIU, Minglu JIN
, doi: 10.11999/JEIT171092
[Abstract](155) [FullText HTML](64) [PDF 1281KB](9)
Information geometry based matrix Constant False Alarm Rate (CFAR) detector is an efficient solution to the intractable issue of target detection for K-distributed sea clutter environment. However, most existing matrix CFAR detectors cost heavy computation complexity, which leads to a limitation in practical application. Based on the Neyman-Pearson criterion, the Likelihood Ratio Test (LRT) is analyzed, the relationship between LRT statistic and the Maximum Eigenvalue is derived, and Matrix CFAR Detection method based on the Maximum Eigenvalue (M-MED) is designed. Simulation results verify that the proposed method can achieve better detection performance with relatively lower computational complexity.
Multi-dimensional Vandermonde Structure Based DOD-DOA and Doppler Frequency Estimation for Bistatic MIMO Radar
Yuanbing CHENG, Linjiang WU, Yu ZHENG, Hong GU
, doi: 10.11999/JEIT171002
[Abstract](98) [FullText HTML](7) [PDF 1239KB](1)
In order to solve the problem of Direction Of Departure (DOD), Direction Of Arrival (DOA) and Doppler frequency estimation in bistatic MIMO radar, a low complexity method is proposed for joint estimation of the three parameters based on the multi-dimensional Vandermonde structure characteristic of the parameter manifold matrices. First, a third-order tensor is constructed according to the multi- dimensional structure of the echo model. Three equivalent matrices are obtained by cutting the tensor along transmit dimension, receive dimension and pulse dimension respectively. Then, combining the multi-dimensional Vandermonde characteristic with the Khatri-Rao product characteristic of the left-singular matrix of the equivalent matrix, transmit manifold matrix, receive manifold matrix and Doppler manifold matrix are estimated. Finally, the DOD, DOA and Doppler frequency are estimated by Root-MUSIC algorithm. Compared with the existence methods, the proposed algorithm improves obviously the estimation precision, and its computational cost is comparable to that of Estimation of Signal Parameters via Rotation Invariant Techniques (ESPRIT) method in small pulse number. The effectiveness of the proposed method is verified by simulation results.
Passive Localization Using TDOA Measurements from Multiple Sensors Based on Priori Knowledge of Target Altitude
Zhaotao QIN, Jun WANG, Shaoming WEI, Yanxian BI, Zixiang WEI
, doi: 10.11999/JEIT171231
[Abstract](134) [FullText HTML](7) [PDF 1611KB](2)
To solve the problem of radiant target localization using Time Difference Of Arrival (TDOA) measurements from multiple sensors, an algebraic closed-form method based on Weighted Least Squares (WLS) minimizations is proposed, with the priori knowledge of target altitude. In near distance scenario, neglecting the effect of earth curvature, the target altitude can be regarded as one-dimensional coordinate of the target. Based on this condition, the target position is solved by a new two-step WLS algorithm. It does not require initial solution guess, and is computationally attractive due to the non-iterative operation. Simulation results show that the target localization accuracy is greatly improved using target altitude, and the proposed method can reach Cramer-Rao Lower Bound (CRLB) accuracy under small Gaussian measurement noise.
An Improved Passive Synthetic Aperture Algorithm Based on Curvilinear Maneuverability of Autonomous Underwater Vehicles
Shenglong JIN, Yu LI, Haining HUANG
, doi: 10.11999/JEIT171225
[Abstract](151) [FullText HTML](16) [PDF 2619KB](3)
In order to overcome difficulty in extending flank array by traditional Extended Towed Array Measurement (ETAM) technique based on curvilinear maneuverability of Autonomous Underwater Vehicles (AUV), a new ETAM method is proposed by combining estimating phase correction factors in beam domain and linear fitting motion compensation in element domain. The method estimates phase differences in beam domain and implements linear fitting of phase correction factors in element domain to compensate phase error due to curvilinear motion, which can acquire accurate phase correction factors and extend array. Results of simulation and experiment show that no matter straight line navigation or curvilinear maneuverability, the method achieved higher DOA estimation accuracy, angular resolution and signal gain, which is also suitable for multi-target resolving. Especially in low signal-noise-ratio condition, the improvement of this method in performance is more obvious, for which it has strong practicality and environmental tolerance.
Recognition and Reconstruction of Conduction Leakage Signal via Power Line Based on PSO-SVM Method
Changlin ZHOU, Zhisheng QIAN, Qinmin WANG, Daojie YU, Junping CHENG
, doi: 10.11999/JEIT171136
[Abstract](177) [FullText HTML](9) [PDF 1600KB](3)
In order to identify the red signal in the conduction leakage signal of the display power line effectively, a Particle Swarm Optimization-Support Vector Mechine (PSO-SVM) algorithm based on Particle Swarm Optimization (PSO) algorithm for parameter optimization is proposed. Firstly, the conducted leakage signal is filtered, then the PSO-SVM is used to train and classify the conducted leakage signals and compared with the SVM classification. Finally, the display image is reconstructed using PSO-SVM. The result shows that the the red signal can be effectively identified, and the identification rate is significantly higher than the SVM classifier.
Aircraft Detection Method Based on Deep Convolutional Neural Network for Remote Sensing Images
Zhi GUO, Ping SONG, Yi ZHANG, Menglong YAN, Xian SUN, Hao SUN
, doi: 10.11999/JEIT180117
[Abstract](22) [FullText HTML](17) [PDF 8079KB](13)
Aircraft detection is a hot issue in the field of remote sensing image analysis. There exist many problems in current detection methods, such as complex detection procedure, low accuracy in complex background and dense aircraft area. To solve these problems, an end-to-end aircraft detection method named MDSSD is proposed in this paper. Based on Single Shot multibox Detector (SSD), a Densely connected convolutional Network (DenseNet) is used as the base network to extract features for its powerful ability in feature extraction, then an extra sub-network consisting of several feature layers is appended to detect and locate aircrafts. In order to locate aircrafts of various scales more accurately, a series of aspect ratios of default boxes are set to better match aircraft shapes and combine predictions deduced from feature maps of different layers. The method is more brief and efficient than methods that require object proposals, because it eliminates proposal generation completely and encapsulates all computation in a single network. Experiments demonstrate that this approach achieves better performance in many complex scenes.
Plane-Wave Compounding with Short-lag Coherence Factor Weighting
Chichao ZHENG, Lunan ZHANG, Hao WANG, Hu PENG
, doi: 10.11999/JEIT180120
[Abstract](17) [FullText HTML](11) [PDF 5267KB](1)
The Coherent Plane-Wave Compounding (CPWC) algorithm is based on the recombination of several plane-waves with different steering angles, which can achieve high-quality images with high frame rate. However, CPWC ignores the coherence between the plane-wave imaging results. Coherence Factor (CF) weighted algorithm can effectively improve the imaging contrast and resolution, while it degrades the background speckle quality. A Short-Lag Coherence Factor (SLCF) algorithm for CPWC is proposed. SLCF uses the angular difference parameter to ascertain the order of the coherence factor and calculates the coherence factor for the plane-waves with small angular difference. Then, SLCF is utilized to weight CPWC to obtain the final images. Simulated and experimental results show that SLCF-weighted algorithm can improve the imaging quality in terms of lateral resolution and Contrast Ratio (CR), compared with CPWC. In addition, in comparison with CF and Generalized Coherence Factor (GCF) weighted algorithm, SLCF can achieve better background speckle quality and it has lower computational complexity.
A High-precision Method of the Rotation Compensation and Cross-range Scaling for ISAR Imaging
Xinge LIU, Mengdao XING, Guangcai SUN
, doi: 10.11999/JEIT171209
[Abstract](139) [FullText HTML](8) [PDF 1987KB](3)
Traditional Inverse SAR (ISAR) imaging algorithms neglect the impact of high-order rotational phase in the signal, which may make ISAR images of a target defocused. Further, the size of a target can not be obtained from ISAR image directly. In this study, an effective method to achieve the rotation compensation and cross-range scaling for ISAR imaging is proposed. Firstly, all the signals of the target are used to form the Local Average Doppler Trend (LADT) signal. Subsequently, RANdom SAmple Consensus (RANSAC) algorithm is performed to estimate the Doppler rate and effective rotational velocity. Finally, high-precision rotation compensation and cross-range scaling can be accomplished. Simulation and real data experiments validate the effectiveness of the proposed method.
Learning-based Localization with Monocular Camera for Light-rail System
Meng YAO, Kebin JIA, Wanchi SIU
, doi: 10.11999/JEIT171017
[Abstract](17) [FullText HTML](6) [PDF 1881KB](2)
The visual-based scene recognition and localization module is widely used in vehicle safety system. This paper proposes a new method of scene recognition based on local key region and key frame, which is based on the problem of large amount of training data, large matching complexity and low tracking precision. The proposed method meets the real-time requirements with high accuracy. First, the method uses the unsupervised method to extract the significant regions of the single reference sequence captured by the monocular camera as the key regions. The binary features with low correlation in key regions are also extracted to improve the scene matching accuracy and reduce the computational complexity of feature generation and matching. Secondly, key frames in the reference sequence are extracted based on the discrimination score to reduce the retrieval range of the tracking module and improve the efficiency. Practical field tests are done on real data of the light railway system in Hong Kong and the open test data set in Nordland. The experimental results show that the proposed method achieves fast matching and the precision is 9.8% higher than SeqSLAM which is based on global feature.
A User Satisfaction Maximization Algorithm Based on Access and Backhaul Integrated Small Base Station
Lun TANG, Yunlong LIU, Xu ZHAO, Runlin MA, Qianbin CHEN
, doi: 10.11999/JEIT171169
[Abstract](26) [FullText HTML](7) [PDF 1555KB](0)
To meet the personal quality requirement of video streaming service under the access and backhaul integrated small base station scene, a user satisfaction maximization algorithm is proposed. The algorithm adjusts dynamically the spectrum resources used for next-cycle queue transmission by analysis the mismatch degree between the actual system reachable rate and user satisfaction demand rate. The corresponding optimization model of the quality satisfaction of all users is established. Then, the Lyapunov stochastic optimization method is used to transform the initial problem into drift plus penalty, the overflow probability constraint is transformed into inequality of variables. Finally, using the proposed user access bandwidth allocation algorithm based on Lagrange dual decomposition and the backhaul and access bandwidth allocation algorithm based on interior point method. The simulation results show that the algorithm can improve the quality satisfaction of all users and ensure the system stability.
Charging Time Minimized Charging Schemes for RF-powered Sensor Network with Moving Trajectory Constrained Mobile Energy Transmitter
Kaikai CHI, Yinan ZHU, Qike SHAO
, doi: 10.11999/JEIT171204
[Abstract](26) [FullText HTML](10) [PDF 1435KB](2)
Radio-Frequency (RF) energy harvesting technique is proved a promising way to solve the short network lifetime issue of traditional Wireless Sensor Networks (WSNs) caused by sensors' finite energy. In the existing charging schemes using the mobile RF Energy Transmitter (ET), ET can move to any location along any moving direction in the monitoring area for energy provision. However, in the practical scenario, ET can only move along the existing roads. For the first time, the charging time minimization issue is considered under the moving trajectory constraint. The Mobile Charging (MC) scheme where ET transmits RF energy while moving and the Static Charging (SC) scheme where ET transmits RF energy while unmoving are proposed, whose the moving trajectory and energy provision time are optimized by the proposed efficient algorithms. Simulation results reveal that the total charging delay of proposed schemes is smaller than the baseline scheme of transmitting energy at turning points. The MC scheme has lower computational complexity but has a slightly larger charging delay as compared to the SC scheme.
Multi-user Grouping Optimization Algorithm Based on Non-orthogonal Multiple Access Systems
Guangfu WU, Tianyin DENG, Kairong SU, Yun LI
, doi: 10.11999/JEIT171220
[Abstract](29) [FullText HTML](7) [PDF 2199KB](1)
As a key part in Non-Orthogonal Multiple Access (NOMA), user grouping is of particular importance for non-orthogonal multiple access system to improve throughput performance and user fairness. When the number of users and the available resources is increased, the optimal scheduling of user grouping will be infeasible, so a multi-user grouping optimization algorithm for different sub-bands is proposed. According to the user channel gain difference and the restrictions of the multiplexed user number in the same subband, the proposed algorithm firstly performs the process of the initial multi-user grouping to reduce the user’s search space. Then, the optimized combination of the initial grouping users is gradually completed, and the maximum geometric mean user throughput is used as user grouping criterion, which can further enhance the cell-edge user throughput. Simulation results show that the system total throughput and geometric mean user throughput performance of the proposed algorithm can be improved by more than 3% compared with the traditional user grouping algorithms.
Multiple to One Fully Homomorphic Encryption Scheme over the Integers
Caifen WANG, Yudan CHENG, Chao LIU, Bing ZHAO, Qinbai XU
, doi: 10.11999/JEIT171194
[Abstract](38) [FullText HTML](11) [PDF 1391KB](2)
Fully homomorphic encryption allows any operation evaluation on encrypted data without decryption. The existing integer-based homomorphic encryption schemes are designed only for two participants namely one party encryption one party decryption (one-to-one), whose computational efficiency is generally low, plaintext space is small, so it can not be applied to big data, cloud computing and other actual scene. Therefore, a full homomorphic encryption scheme with multi-party encryption, one party decryption (multiple to one) is presented. The scheme simplifies the key generation process on the basis of guaranteeing the security, but also gives the range of the number of encrypted parties that can be decrypted accurately in the process of homomorphic operation. Meanwhile, in the random oracle model, the security of the new scheme is proved based on approximate Greatest Common Divisor (GCD) problem. Numerical analysis demonstrates that the presented scheme can not only extend the data traffic, but also improve the efficiency by comparing with the existing schemes. Simulation results show that proposed scheme is more practical in the range of integer, and meets the requirements of the users to the system response. Finally, the plaintext space is expanded to 3 bit, comparing and analysing the experiment with the scheme of 1 bit.
Packet Forwarding Authentication Mechanism Based on Cipher Identification in Software-defined Network
Xi QIN, Guodong TANG, Chaowen CHANG, Ruiyun WANG
, doi: 10.11999/JEIT171226
[Abstract](22) [FullText HTML](9) [PDF 1353KB](1)
To deal with the lack of a secure and efficient data source authentication mechanism in Software-Defined Network (SDN), a packet forwarding authentication mechanism based on cipher identification is proposed. Firstly, a packet forwarding authentication model based on cipher identification is established, where the cipher identification is identified as a passport of IP packets entering and leaving the network. Secondly, the SDN batch anonymous authentication protocol is designed to decentralize the authentication function of the SDN controller to the SDN switch. The SDN switch performs user authentication and cipher identification verification, and quickly filters forgery, falsification, and other illegal packets to improve the unified authentication and management efficiency of the SDN controller, while providing users with the conditions of privacy protection. Thirdly, a scheme for sampling and verifying packets based on cipher identification in any node is proposed, where any attacker can not bypass the packet detection by inferring the sample, to ensure the authenticity of the packet while reducing its processing delay. Finally, safety analysis and performance evaluation are conducted. The results show that this mechanism can quickly detect packet falsification and tampering and resist ID analysis attacks, but at the same time it introduces about 9.6% forwarding delay and less than 10% communication overhead.
Cognitive Radio Network Downlink Power Allocation and Beamforming Method with Imperfect Channel State Information
Zhongheng JI, Xinsheng JI, Kaizhi HUANG
, doi: 10.11999/JEIT171135
[Abstract](62) [FullText HTML](6) [PDF 1163KB](0)
Some problems of multi-user downlink power allocation and beamforming in a underlay Cognitive Radio Network (CRN) with imperfect Channel State Information (CSI) are addressed. They include ignoring the interferences of the Primary Network (PN) to the Secondary Users (SU), conventional SDR algorithm of convex optimization needing the constraint approximation, the high complexity of the algorithm, and implemented with difficulty, etc. Firstly the term of interference of the PN to the SU is added to the CRN model. The optimization problem is formulated with the worst-case imperfect CSI. Next the constraints of the problem are transformed by means of Lagrange duality. Then, based on the form of the problem, the simple, fast and practical iterative algorithm is obtained by utilizing the duality of uplink-downlink, introducing virtual power, and transforming the optimization problem into the problem of uplink power allocation and beamforming. Numerical simulation results show that it converges faster. It is also found that the errors of the imperfect CSI not only influence the downlink power but also change the feasibility region. The variation of transmitting power of the PN Base Station (PBS) could affect the feasibility region notably.
Research on Multi-source and Asynchronous Data Fusion of Target Trajectory Based on the Modif ied Ensemble Kalman Filter Method
Zequn ZHANG, Wenjuan REN, Kun FU, Jifei FANG, Yue ZHANG
, doi: 10.11999/JEIT171115
[Abstract](79) [FullText HTML](9) [PDF 1194KB](4)
A modified Ensemble Kalman Filter (EnKF) theory model based on kinematic equations is proposed to realize the historical fitting analysis and trajectory prediction of the target trajectory in the multi-source observation data scenario. This model is applied to accurately calculate the target motion state parameters (velocity and acceleration), then the target’s follow-up movement is predicted. The multi-source observation data fusion is realized by using the EnKF, which enables the low-precision observation data to be corrected by high-precision observation data, and the accuracy of the corrected data can be calibrated by the statistical information provided by the EnKF.
Topology Based Caching Optimizing Strategy in Named Data Networking
Xin WEI, Yong YAN, Shaoyong GUO, Zhuo YU, Xuesong QIU
, doi: 10.11999/JEIT170967
[Abstract](23) [FullText HTML](8) [PDF 1318KB](0)
In order to utilize storage space and fetch content effectively in Named Data Networking (NDN), this paper constructs a model for caching problem and proposes a greedy algorithm based on topology information. To optimize the algorithm, content popularity is introduced into execution. Furthermore, content hit distance is shortened effectively. This paper simulates a NDN network based on some real topology data with ndnSIM, and compares the proposed algorithm with traditional prob algorithm, default Cache Everything Everywhere (CEE) algorithm and degree based Heterogeneous Storage Size (HSS) algorithm through simulation. The results show that the algorithm proposed in this paper has better performance.
Frequency Locator Polynomial Based Fast Algorithm for Sparse Aliased Spectrum Recovery
Kai CAO, Peizhong LU, Yan ZOU, Lin LING
, doi: 10.11999/JEIT171152
[Abstract](77) [FullText HTML](7) [PDF 1030KB](0)
A fast algorithm based on Frequency Locator Polynomial (FLP) for sparse spectrum recovery is proposed. Using the shifted subsampled signals, the FLPs are constructed, thus to locate rapidly the nonzero frequencies. In particular, the nonlinear problem of sparse spectrum recovery is converted into solving a series of linear equations. Experimental results show that the proposed algorithm exhibits higher processing speed and lower error spectrum reconstruction rate than its predecessor BigBand.
Visual Tracking Algorithm Based on Global Context and Feature Dimensionality Reduction
Yanjing SUN, Sainan WANG, Yunkai SHI, Xiao YUN, Wenjuan SHI
, doi: 10.11999/JEIT171143
[Abstract](94) [FullText HTML](8) [PDF 2972KB](3)
Tracking effects of algorithms using correlation filter are easily interfered by deformation, motion blur and background clustering, which can result in tracking failure. To solve these problems, a visual tracking algorithm based on global context and feature dimensionality reduction is proposed. Firstly, the image patches uniformly around the target are extracted as negative sample, and thus the similar background patches around the target are suppressed. Then, an update strategy based on principal component analysis is proposed, constructing the matrix to reduce the dimensionality of HOG feature, which can reduce the redundancy of feature when it updates. Finally, the color features are added to represent the motion target and the response of the system states are adaptively fused according to the features. Experiments are performed on recent online tracking benchmark. The results show that the proposed method performs favorably both in terms of accuracy and robustness compared to the state-of-the-art trackers such as Staple or KCF. When deformation occur, the proposed method is shown to outperform the Staple tracker and KCF algorithm by 8.3% and 13.1% respectively in median distance precision.
Flow Characteristics Aware Dynamic Controller Assignment in Software-defined Networking
Shaojun ZHANG, Julong LAN, Yiming JIANG, Penghao SUN
, doi: 10.11999/JEIT171149
[Abstract](93) [FullText HTML](10) [PDF 1421KB](2)
In Software-Defined Networking (SDN) with distributed control plane, the switches are assigned to controllers using only the quantity distribution of flow requests as the basis of resource allocation. To address this issue, the control resource consumption of flow requests processing with different characteristics is analyzed taking the source and destination of flow as an example, from which a conclusion is drawn that the characteristics distribution of flow should be taken into account when allocating control resource. Then, a flow characteristics aware controller assignment model is designed, and a fast algorithm coping with the fluctuation of flow request is proposed. Simulation results show that when solving with the simulated annealing algorithm, the model can save 10%~20% of control resource compared with the load balancing model; with 10% of resource saving, the proposed algorithm outperforms the simulated annealing algorithm in execution speed and scalability.
Secrecy Polar Coding in Systems with Probabilistic DF Relay
Huiqing BAI, Liang JIN, Kaizhi HUANG, Ming YI
, doi: 10.11999/JEIT171142
[Abstract](90) [FullText HTML](4) [PDF 1455KB](0)
A relay aided secrecy polar coding method is proposed for the communication systems where the relay uses Decode-and-Forward (DF) in probability. It ensures the transmission reliability and improves the secrecy rate. First, the transmitter encodes the secrecy bits in two layers: the first layer is designed over the virtual Binary Erasure Channel (BEC) that generated by the probabilistic DF relay, and the second layer is designed over the real transmission channels. After receiving the codeword, relay decodes and extracts the frozen bits which the legitimate user can not obtain directly in probability, and re-encodes them by classical secrecy polar coding. Finally, the receiver decodes the received codewords from the relay and the transmitter in turn. The theory and simulation results verify that the legitimate user is able to decode reliable, while the eavesdropper can not obtain any information about the secrecy bits. Moreover, the secrecy rate increases as the code length and the relay forwarding probability increase, and it outperforms the classical secrecy polar coding method.
Atmosphere Refractive Error Correction Method Based on Ray Tracing Differential Form
Peipei WEI, Xiaoyan DU, Changyin JIANG
, doi: 10.11999/JEIT171131
[Abstract](45) [FullText HTML](24) [PDF 2428KB](3)
Atmosphere refraction error is a main error factor to affect synchronization accuracy, tracing accuracy, navigation accuracy and positioning accuracy for various radio systems. On the basis of geometrical optics, the ray tracing method can precisely make this error correction. For the problem that traditional ray tracing method can not deal with the abnormal atmosphere, ray tracing differential form is derived and then a correction method suitable for arbitrary atmosphere is proposed. The tracing data from ground station are taken to test this method. In addition, the refractive error in evaporation duct is compared with that in standard atmosphere. The results show that the refractive error of radio wave trapped entirely in the duct has the biggest influence. The proposed method provides technique support for improving the measurement precision of radio system in arbitrary atmosphere.
Reconfigurable Hardware Task Scheduling Algorithm Based on 3D Fragmentation Layout Strategy
Jinfu XU, Lu LIU, Wei LI, Longmei NAN
, doi: 10.11999/JEIT171205
[Abstract](43) [FullText HTML](30) [PDF 2470KB](1)
The existing hardware task scheduling algorithms describe task imperfectly and ignore the compactness of time dimension. The task downloading time is considered for improving the task attribute, and the 3D-resource model with the two dimensional resource of device and time is established, in order to abstract the issue of task layout into a special three-dimensional space placement issue. With this model, it is concluded that the existing algorithms can not overcome the unpredictability of the task and the diversity of resource occupancy, leading low scheduling success rate and resource utilization rate. To solve the problem, a three dimensional reconfigurable task scheduling algorithm called 3D_RTSA is proposed. A scheduling strategy based on task urgency and a layout strategy based on 3D fragmentation are designed and implemented. Compared with the other 4 algorithms, the results show that the scheduling success rate of 3D_RTSA is 3%, 21%, 28%, 35% higher than that of GC, Look-aheadest, SPSA and DTI algorithms under the condition of heavy load and small task C30, and the utilization ratio of resources is 5% and 18% higher than that of Look-aheadest and SPSA algorithm under the condition of light load and large task C50. Besides, the time complexity of the algorithm is not increased.
Fuzzy Clustering Ensemble Model Based on Distance Decision
Bowen FEI, Yunfei QIU, Wanjun LIU, Daqian LIU
, doi: 10.11999/JEIT171065
[Abstract](47) [FullText HTML](32) [PDF 1474KB](3)
Fuzzy clustering is a kind of clustering algorithm which shows superior performance in recent years, however, the algorithm is sensitive to the initial cluster center and can not obtain accurate results of clustering for the boundary samples. In order to improve the accuracy and stability of clustering, this paper proposes a novel approach of fuzzy clustering ensemble model based on distance decision by combining multiple fuzzy clustering results. First of all, performing several times clustering for data samples by using FCM (Fuzzy C-Means), and corresponding membership matrices are obtained. Then, a new method of distance decision is proposed, a cumulative distance matrix is constructed by the membership matrices. Finally, the distance matrix is introduced into the Density Peaks (DP) algorithm, and the final results of clustering are obtained by using the improved DP algorithm for clustering ensemble. The results of the experiment show that the clustering ensemble model proposed in this paper is more effective than other classical clustering ensemble model on the 9 data sets in UCI machine learning database.
A One-dimensional Discrete Map Chaos Criterion Theorem with Applications in Pseudo-random Number Generator
Hongyan ZANG, Jiu LI, Guodong LI
, doi: 10.11999/JEIT171139
[Abstract](60) [FullText HTML](33) [PDF 1973KB](12)
A novel one-dimensional discrete chaotic criterion is firstly constructed by studying the modular operation of the discrete dynamical systems. The judgement of the Marotto theorem is used to prove that the suggested dynamical systems are chaotic. Secondly, several special chaotic systems satisfied with the conditions of this paper are given, and the bifurcation diagram and Lyapunov exponential spectrum are also analyzed. Numerical simulations show that the proposed chaotic systems have the positive Lyapunov exponent, which indicates the accuracy of the proposed theory. Additionally, a Pseudo-Random Number Generator (PRNG) is also designed based on the given new chaotic system. Using SP800-22 test suit, the results show that the output sequence of PRNG has good pseudorandom. Finally, as an application of the PRNG, an image encryption algorithm is given. The proposed encryption scheme is highly secure Key space of 2747 and can resist against the statistical and exhaustive attacks based on the experimental results.
A Fast Algebraic Decoding of the (41, 21, 9) Quadratic Residue Code
Yi WU, Chunlan LUO, Xinqiu ZHANG, Xiao LIN, Zhexin XU
, doi: 10.11999/JEIT170983
[Abstract](71) [FullText HTML](40) [PDF 478KB](4)
In order to reduce the computational complexity of computing unknown syndromes for the coefficients of the error-locator polynomial and reduce the decoding time when one is decoding, this paper proposed an algebraic decoding algorithm of (41, 21, 9) QR code without calculating the unknown syndromes by solving the Newtonian identity. Simultaneously, an objective theoretical analysis of the computational complexity is given for the part of improvement. Besides, this paper also puts forward the simplifying conditions to determine the number of errors in the received word, which in order to further reducing the decoding time. Simulation results show that the proposed algorithm reduces the decoding time with maintaining the same decoding performance of Lin’s algorithm.
An Improved Spectral Clustering Algorithm Based on Axiomatic Fuzzy Set
Xiaoqiang ZHAO, Xiaoli LIU
, doi: 10.11999/IEIT170904
[Abstract](67) [FullText HTML](27) [PDF 1744KB](1)
Gaussian kernel is usually used as the similarity measure in spectral clustering algorithm, and all the available features are used to construct the similarity matrix with Euclidean distance. The complexity of the data set would affect its spectral clustering performance. Therefore, an improved spectral clustering algorithm based on Axiomatic Fuzzy Set (AFS) is proposed. Firstly, AFS algorithm is combined to measure the similarity of more suitable data by recognizing features, and the stronger affinity matrix is generated. Then Nyström sampling algorithm is used to calculate the similarity matrix between the sampling points and the sampling points and the remaining points to reduce the computational complexity. Finally, the experiment is carried out by using different data sets and image segmentations, the effectiveness of the proposed algorithm are proved.
A Co-planar Waveguide Fed Dual Band-notched Tapered Slot Antenna
Zhenya LI, Xiaosong ZHU, Jianhua ZHANG
, doi: 10.11999/JEIT171055
[Abstract](53) [FullText HTML](17) [PDF 1865KB](1)
In order to filter out the interference of WIMAX (3.3~3.8 GHz) and WLAN (5.125~5.825 GHz) narrowband signals to Ultra WideBand(UWB) system, a Co-Planar Waveguide (CPW) fed miniaturized tapered slot antenna with dual band-notched characteristics is proposed. The CPW structure can effectively extend the bandwidth of the antenna and realize the full coverage of the whole UWB (3.1~10.6 GHz) frequency band. The dual band-notched characteristics (3.15~3.97 GHz and 4.94~6.05 GHz) are effectively achieved by etching the L-shaped slot in the antenna feeder and opening a pair of E-shaped slots in the radiating patch, which can inhibit WIMAX and WLAN interference to the UWB system. The antenna is simple and compact, and the size is very small, only 40 mm×18 mm×0.813 mm. The simulated and measured results show that the antenna has good notch and gain characteristics in the ultra wideband band, and can be used in miniaturized UWB system. The method has certain reference significance for the research of notched tapered slot antenna.
Kernel Extreme Learning Machine Based on K Interpolation Simplex Method
Yidan SU, Ruoyu LI, Hua QIN, Qin CHEN
, doi: 10.11999/JEIT171104
[Abstract](71) [FullText HTML](27) [PDF 1016KB](1)
The kernel Extreme Learning Machine (ELM) has a problem that the kernel parameter of the Gauss kernel function is hard to be optimized. As a result, training speed and classification accuracy of kernel ELM are negatively affected. To deal with that problem, a novel kernel ELM based on K interpolation simplex method is proposed. The training process of kernel ELM is considered as an unconstrained optimal problem. Then, the Nelder-Mead Simplex Method (NMSM) is used as an optimal method to search the optimized kernel parameter, which improves the classification accuracy of kernel ELM. Furthermore, the K interpolation method is used to provide appropriate initial values for the Nelder-Mead simplex to reduce the number of iterations, and as a result, the training speed of ELM is improved. Comparative results on UCI dataset demonstrate that the novel ELM algorithm has better training speed and higher classification accuracy.
Design of the Diversity Phased Array Based on Collision Avoidance Radar
Yao TANG, Bo LI, Zicheng DU
, doi: 10.11999/JEIT171121
[Abstract](151) [FullText HTML](107) [PDF 2566KB](14)
Conventional phased array radar transmits coherent signal to form antenna pattern. By transmitting and receiving antenna reuse its aperture is always less than MIMO radar. This paper firstly analyses the same points and the difference between MIMO radar and phased array radar. It further points out that the essential advantage of MIMO radar is the digital transmitting beam forming. Second it designs a diversity phased array radar in collision avoidance atmosphere. Its transmitting part uses phase array system, while the receiving part uses the Digital BeamForming (DBF). Through the analysis for the limitation of the digits phase shifter, it proves that this radar can achieve the same virtual aperture performance as MIMO radar, while the rader can avoid to produce the orthogonal signal. Finally through the computer simulation it verifies the feasibility and effectiveness of the method. This radar system can effectively reduce the cost and improve channel consistency under the premise of promised beam width.
A Novel Automatic Registration Method for Fluorescein Fundus Angiography Sequences Based on Mutual Information
Xiaoyan LIU, Haohao WANG, Gang SUN, Pu ZHANG, Min LIU, Ling GAO
, doi: 10.11999/JEIT170868
[Abstract](91) [FullText HTML](35) [PDF 3053KB](4)
Fluorescein Fundus Angiography (FFA) is regarded as the golden diagnostic criteria for fundus diseases. However, dislocation or rotation of the interested images on anatomic landmark (like retinal vascular branches, neovascularization), caused by inevitable eyeball movement, brings about difficulties in subsequent quantitative analysis and progress assessment of the diseases. In order to solve the above problems, a novel method based on mutual information is proposed for automatic registration of FFA image sequence. Firstly, the vessels of image sequence are segmented by multi-scale linear filter and down sampled hereafter by image pyramid. Then, the similarity of sampled images is calculated by mutual information and the evolution strategy is adopted to optimize the registration parameters. Finally, the transformation matrix with maximum mutual information is obtained to register the FFA image. Tests with FFA image sequences of 4 patients (total 1039 frames) show that the overall registration rate of the algorithm reaches 93% and the failure rate is only 1%. Compared with the classical registration methods, the proposed method shows better comprehensive performance in terms of registration rate, computing speed as well as robustness. It lays basic foundations for quantitative analysis on FFA images and potential clinical application.
Concatenated Polar Codes Scheme Based on Segmented Puncturing
Yang CAO, Han ZHANG, Qiaoling TU, Xiaohong LI, Xiaofeng PENG
, doi: 10.11999/JEIT171113
[Abstract](263) [FullText HTML](155) [PDF 1690KB](15)
Polar codes have outstanding error correction performance, but the code length of conventional polar codes is not compatible because of their coding method. To construct rate-compatible polar codes, a segmented puncturing method is proposed. Using the rate of polarization, the puncturing effect is measured and the codeword is removed to make the largest rate of polarization, which is the optimal puncturing mode. As the first codeword of the optimal puncturing mode is 0, the parity check codes are introduced to detect the decoding error of preceding segments codeword. The decoding performance of the method is simulated, results show that this method can obtain about 0.7 dB coding gain at 10–3 bit error rate compared with the traditional puncturing method, which can effectively improve the performance of the punctured polar codes.
Multi-target Localization Method for Bistatic MIMO Radar Using Nonuniform Rectangular Array
Zhidong ZHENG, Honggang YUAN
, doi: 10.11999/JEIT171036
[Abstract](85) [FullText HTML](19) [PDF 1105KB](3)
A new algorithm is proposed to estimate jointly the four parameters (EDOD, ADOD, EDOA, ADOA) of targets based on the double-extension of aperture degree of freedom by combining MIMO technique with Minimum redundancy array under the conditions of non-uniform rectangular array configurations both on transmitter and receiver. Firstly, the two permutation matrices are constructed by utilizing the operational properties of the Khatri-Rao product of multiple matrices. Then the new data which possesses the characteristics of the double-extension of degree of freedom is attained by performing the twice row permutating, the redundant items deleting, multi-dimensional smoothing and data folding operations on the received data. The results illustrate that: the proposed method can estimate the four parameters of targets efficiently, and the estimated parameters are paired automatically without extra pairing operation. The parameter estimation performance of the proposed method is better than those of the ALS and multi-dimension ESPRIT methods under the same simulation conditions. And the proposed method can provide much stronger parameter identifiability than the conventional ones.
Identity Based Dynamic Key Management of Airborne Ad Hoc Network
Hong WANG, Jianhua LI, Chengzhe LAI
, doi: 10.11999/JEIT171148
[Abstract](101) [FullText HTML](26) [PDF 1477KB](4)
Because of nowadays airborne network’s updating difficulty of pre-allocated symmetrical key, high communication cost of public key certificate and the requirement of security channel for distributed identity-based key management, identity-based dynamic key management of airborne network is proposed. It is composed of two algorithms: self-organized generation of master key without the trusted third party and distributed management of user’s private key. Moreover, the master key share and user private partition can be delivered without the pre-established security channel by blinding them so that the scheme is easy to develop and flexible to extend. Finally, the correctness and security of the proposed scheme are proved, it is shown that it can provide the ability to resist the impersonation attack, replay attack and man-in-the-middle attack.
Equivalent Circuit Method for Hexagonal Loop Composite Absorbing Material
Jiaao YU, Shirui PENG, Xiaokun CHEN, Youquan LI
, doi: 10.11999/JEIT171103
[Abstract](164) [FullText HTML](66) [PDF 5734KB](3)
An equivalent circuit method of performance estimation for hexagonal loop composite absorbing metamaterial is proposed, and the corresponding equivalent circuit model is established. Based on the Fourier analysis of hexagonal lattice distribution, the equivalent distribution periodic parameter is proposed and the estimation method of RLC parameters is given according to the size of units. The applicability and accuracy of the equivalent circuit model for several structure dimensions are verified and compared with HFSS. A sample is fabricated and measured for further verification, which has a good broadband radar absorbing performance in 1.7~5.7 GHz.
Online Mapping Algorithm Based on Reliability for 5G Network Slicing
Lun TANG, Guofan ZHAO, Heng YANG, Peipei ZHAO, Qianbin CHEN
, doi: 10.11999/JEIT171119
[Abstract](145) [FullText HTML](44) [PDF 1562KB](6)
To meet the diversified demand of 5G Network Slicing (NS), while ensuring the reliability of slice, to achieve the optimal allocation of network resources, considering the dynamic mapping and lightweight reliable mapping problem of network slicing, this paper proposes a joint allocation scheme of computing resources, link resources and the spectrum resources of Radio Remote Unit (RRU). Firstly, a multi-objective resource allocation model oriented to reliability constraints is established, and the Lyapunov optimization model is introduced to ensure the queue stability and optimize the resource allocation. Then, the virtual node mapping algorithm based on queue stability and virtual link mapping algorithm based on reliability are proposed. Finally, the time is discretized into a series of continuous time windows, and the online network slice mapping algorithm is implemented by using the time window dynamic processing of the incoming network slice request. Simulation results show that the proposed algorithm improves resource utilization and guarantees network reliability.
Privacy Preserving Method Based on Location Service in Personalized Search
Qiang ZHANG, Guojun WANG
, doi: 10.11999/JEIT171137
[Abstract](112) [FullText HTML](14) [PDF 1894KB](0)
For personalized search based on location service, the trusted third-party server and peer node are used as the main method for privacy preserving. However, entirely trusted third-party server or peer node does not exist in real life. In order to address this problem, a method of privacy preserving on the location of mobile users is proposed when using personalized search. The method is used to convert the user’s location information into distance information and generate the user model according to the user’s query type, forming a query matrix with user location information, then the matrix is used to encrypt the user’s query and conceal the user information in the query matrix. Finally, according to the calculation of the security inner product, the K file with the highest relevance score is returned to the user. It is evident from the security analysis that the proposed method can effectively protect the user’s query privacy and location privacy. The analysis and experimental results show that the proposed method can greatly shorten the time of index construction and reduce the communication overhead. While providing users with location based personalized search results, the method is able to remedy the defects of small-screen mobile devices.
Beam Performance and Optimization Method for Meter-wave Frequency Diverse MIMO Radar in Multipath Scenario
Xingxing LI, Dangwei WANG, Xiaoyan MA
, doi: 10.11999/JEIT171030
[Abstract](132) [FullText HTML](26) [PDF 2062KB](4)
Traditional meter-wave radar usually suffers from the problem of Beam Split (BS) and Radar Blind Area (RBA) in the situation of low-grazing angle. To alleviate this difficulty, a Frequency Diverse Subaperturing Multiple-Input Multiple-Output (FDS-MIMO) radar is proposed and a theoretical framework for the analytical investigation of multipath characteristics is presented. The specular and perturbational multipath model is built, along with closed-form expression of the joint transmit-receive beampattern gain. Moreover, a notional concept of Multipath Mitigation Area (MMA) is defined together with the corresponding boundary conditions, and the Low Observability Rate (LOR) is defined as a performance benchmarkan to evaluate the FDS-MIMO radar beam overage capability. Next, the FDS-MIMO radar low-altitude beam coverage performance is optimized according to the soutions of the boundary conditions. Both theoretical analysis and numerical results demonstrate the advantages of FDS-MIMO radar over the conventional phased-MIMO radar in terms of low altitude beam coverage performance, and the BS and RBA of meter-wave radar is decreased by ultilizing the range-dependent beampattern.
MEMS-based Three-dimensional Electric Field Sensor with Low Cross-axis Coupling Interference
Biyun LING, Chunrong PENG, Ren REN, Zhaozhi CHU, Zhouwei ZHANG, Hucheng LEI, Shanhong XIA
, doi: 10.11999/JEIT171188
[Abstract](64) [FullText HTML](22) [PDF 3151KB](2)
Cross-axis coupling interference influences greatly the measurement accuracy of Three-Dimensional (3D) Electric Field Sensor (EFS). A MEMS-based One-Dimensional (1D) Electric Field Microsensor (EFM) chip with low coupling interference is presented, and a MEMS-based 3D EFS with low cross-axis coupling interference is developed by arranging three 1D EFM chips orthogonally. Different from previously reported 1D EFM chips sensitive to perpendicular electric field component, the proposed 1D EFM chip is designed to be symmetrical and connected to difference circuit, so that it is capable of sensing parallel electric field component perpendicular to axis of symmetry and eliminating coupling interference. The proposed 3D EFS has the advantages of small size and high integration. Experimental results reveal that in the range of 0~120 kV/m, the cross-axis sensitivities are within 3.48%, and the total measurement errors of this 3D EFS are within 7.13%.
Compensative Coherent Processing Algorithm for Short Pulse Non-coherent Radar
Haibo WANG, Wenhua HUANG, Yue JIANG
, doi: 10.11999/JEIT171147
[Abstract](104) [FullText HTML](23) [PDF 846KB](5)
Based on the characteristics of short pulse non-coherent radar, the parameterized signal model is established. By analysis on the reasons of no-coherence, compensative coherent processing algorithm based on matching filter and parameter estimation is proposed. The rationality of the compensative coherent processing is proved by the mathematical derivation as to single point target. Then, requirement for the range extended target is analyzed in theory, in the condition of approximate compensative coherent processing. Finally, the theoretical analysis results are verified by simulation.
Time Series Method Clustering in User Behavior Based on Symmetric Kullback-Leibler Distance
Wenjing LI, Xiangjian ZENG, Meng LI, Peng YU
, doi: 10.11999/JEIT180016
[Abstract](29) [FullText HTML](32) [PDF 1518KB](12)
Behavioral analysis of Internet users over time is a hot spot in user behavior analysis in recent years, usually clustering users is a way to find the feature of user behavior. Problems like poor computing performance or inaccurate distance metric exist in present research about clustering user time series data, which is unable to deal with large scale data. To solve this problem, a method for clustering time series in user behavior is proposed based on symmetric Kullback-Leibler (KL) distance. First time series data is transformed into probability models, and then a distance metric named KL distance is introduce, using partition clustering method, the different time distribution between different users. For the Large-scale feature of physical network data, each process of clustering is optimized based on the characteristics of KL distance. It also proves an efficient solution for finding the clustering centroids. The experimental results show that this method can improve the accuracy of 4% compared with clustering algorithm using the Euclidean distance metric or DTW metric, and the calculation time of this method is less a quantity degree than clustering algorithm using medoids centroids. This method is used to deal with user traffic data obtained in physical network which proves its application value.
Aircraft Target Classification and Recognition Algorithm Based on Measured Data
Ming LI, Jiaojiao WU, Lei ZUO, Wanjie SONG, Huimin LIU
, doi: 10.11999/JEIT180024
[Abstract](26) [FullText HTML](27) [PDF 2071KB](12)
After analyzing the features of three measured data from the low-resolution radar system, corresponding to the helicopter, the propeller, and the turbojet, an algorithm is proposed by using multiple features to classify and recognize the aircraft targets. First, multiple features are extracted, including Doppler frequency shift, relative magnitude, waveform entropy of time and frequency domain, and time-frequency domain features from the measured data. Then, these features are utilized for classification purpose by means of the Support Vector Machine (SVM). Finally, owing to the symmetry and the width of time-frequency distributions of the returned signals between the helicopters with odd and even blades, a method is proposed to recognize of helicopter. The experimental results of measured data verify the effectivity of the proposed algorithms.
Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming
Changqiang HUANG, Kexin ZHAO, Bangjie HAN, Zhenglei WEI
, doi: 10.11999/JEIT180068
[Abstract](27) [FullText HTML](19) [PDF 1299KB](5)
To solve the problem of dimension disaster when solving air combat maneuvering decision-making by dynamic programming, a swarm intelligence maneuvering decision-making method based on the approximate dynamic programming is proposed. Firstly, the Unmanned Aerial Vehicle (UAV) dynamic model and advantage functions of situation are established. On this basis, air combat process is divided into several stages according to dynamic programming thought. In order to reduce the search space, an Artificial Potential Field (APF) Guiding Ant Lion Optimizer (ALO) approximate optimal control amount is adopted in each programming stage. Finally, by comparing expert system, the experiment result indicates that the high dynamic and real-time air combat maneuvering decision can be solved by the proposed method effectively.
Two-dimension Space-variance Correction Approach for Diving Highly Squinted SAR Imaging with Sub-aperture
Yanfeng DANG, Yi LIANG, Bowen BIE, Jinshan DING, Yuhong ZHANG
, doi: 10.11999/JEIT180021
[Abstract](15) [FullText HTML](10) [PDF 2556KB](2)
The diving SAR usually adopts the highly squint mode and sub-aperture to satisfy maneuvering and the real-time processing. However, the existence of severe range-azimuth coupling, range-dependent squint angle and three-dimension velocity and acceleration leads to the space variance of range envelope and azimuth phase, which makes imagery unfocused seriously. To solve these problems, a Two-stage Frequency Filtering Algorithm (TsFFA) is proposed. After preprocessing, the First-stage Frequency Filtering (FsFF) factor is first introduced to correct azimuth-dependent Range Cell Migration (RCM) and realize the unified RCM correction. Furthermore, the Second-stage Frequency Filtering (SsFF) factor is adopted to equalize azimuth-dependent Doppler parameters and realize unified azimuth phase focused. Simulation results are presented to validate the effectiveness of the proposed approach.
Investigation on PRI Variation for High Squint Spaceborn Spotlight SAR
Pei WANG, Wei XU, Ning LI, Weidong YU
, doi: 10.11999/JEIT180049
[Abstract](24) [FullText HTML](12) [PDF 3390KB](1)
High squint spotlight mode of spaceborne SAR can be used to achieve high resolution and wide swath, and also can be used to acquire information of target from multi-azimuth. However, the considerable range migration can result in efficiency decreasing in data acquisition, and dilemma in system design. This problem can be solved by the technology named PRI (Pulse Repetition Interval) variation which can track the slant range variation of the target during data acquisition. In this paper, the principle of PRI variation is studied, and methods of PRI sequence iterative design and system parameter selection are proposed. Two approaches to reconstruct the nonequal spaced and nonperiod data in azimuth sampling are compared. Finally, the first results of PRI variation mode of airborne SAR experiment with high slant spotlight mode are presented.
Efficient Offline/Online Attribute Based Encryption with Verifiable Outsourced Decryption
Zhiyuan ZHAO, Lei SUN, Jiafu HU, Shie ZHOU
, doi: 10.11999/JEIT180122
[Abstract](19) [FullText HTML](9) [PDF 1062KB](1)
Attribute based encryption can provide data confidentiality protection and fine-grained access control for fog-cloud computing, however mobile devices in fog cloud computing system are difficult to bear the burdensome computing burden of attribute based encryption. In order to address this problem, an offline/online ciphertext-plicy attribute-based encryption scheme is presented with verifiable outsourced decryption based on the bilinear group of prime order. It can realize the offline/online key generation and data encryption. Simultaneously, it supports the verifiable outsourced decryption. Then, the formal security proofs of its selective chosen plaintext attack security and verifiability are provided. After that, the improved offline/online ciphertext-plicy attribute-based encryption scheme with verifiable outsourced decryption is presented, which reduces the number of bilinear pairings from linear to constant in the transformation phase. Finally, the efficiency of the proposed scheme is analyzed and verified through theoretical analysis and experimental simulation. The experimental results show that the proposed scheme is efficient and practical.
Study on Multi-target Angle Tracking Algorithm of Bistatic MIMO Radar with Unknown Target Number
Zhengyan ZHANG, Jianyun ZHANG, Qingsong ZHOU
, doi: 10.11999/JEIT171174
[Abstract](26) [FullText HTML](10) [PDF 1633KB](7)
In order to solve the angle tracking problem of bistatic MIMO radar when the number of target is unknown, a joint tracking algorithm of the number of target and the angle is proposed. There is no variable in Adaptive Asymmetric Joint Diagonalization (AAJD) algorithm that can directly represent the eigenvalue. Therefore, the idea of principal component sequence estimation is introduced to the improved AAJD algorithm, and the eigenvalues are iteratively evaluated. Then, the number of target is estimated by using the improved information theory. Secondly, the anti-dithering algorithm of target number is proposed, which improves the robustness of the algorithm. Finally, the ESPRIT algorithm is improved to realize the automatic matching and association of DOD and DOA. The simulation results show that the improved AAJD algorithm can successfully track the number of target and angle trajectories. The efficiency of the proposed method is verified.
Design of Wideband Patch Antenna Array with Low RCS Performance Based on Metasurface
Siming WANG, Jun GAO, Xiangyu CAO, Yuejun ZHENG, Junxiang LAN
, doi: 10.11999/JEIT171184
[Abstract](22) [FullText HTML](8) [PDF 4466KB](2)
A wideband patch antenna array with low Radar Cross Section (RCS) based on metasurface is proposed. The 2×4 antenna array is composed of two kinds of slotted patch antennas working at different frequency band, realizing the miniaturization and bandwidth broadening of the antenna array. Then, based on the phase cancellation principle, low RCS performance is realized owing to the metasurface consisting of two Artificial Magnetic Conductor (AMC) structures in chessboard configuration. Simulated and measured results show that the working frequency band is expanded from 5.7~6.2 GHz to 5.6~6.6 GHz and radiation performance remains well with metasurface added to. Meanwhile the antenna monostatic RCS is reduced significantly. 3 dB RCS reduction is achieved over the range of 5.3 GHz to 7.0 GHz and the peak reduction is up to 31 dB under X polarization. While the 3 dB RCS reduction range is 5.8~6.9 GHz under Y polarization.
BeiDou Navigation Satellite System in Challenge Environment Using an Atomic Clock and Barometric Altimeter
Bo LI, Chao XU, Xiaohui LI, Huijun ZHANG, Wenli WANG
, doi: 10.11999/JEIT171181
[Abstract](38) [FullText HTML](12) [PDF 1694KB](4)
The vertical positioning accuracy of BeiDou satellite navigation System (BDS) and the continuity of receiver in the challenge environment can not satisfy the user demand. If atomic clocks are used in the receiver, the high stability of the atomic clock can be used for long time and high precision prediction of receiver clock bias. The positioning accuracy and continuity are improved by using atomic clock and barometric altimeter. This article first analyzes the atomic clocks and barometric altimeter aided BDS positioning algorithm; Then, correction method is proposed for initialization of barometric altimeter, and analysis on the difference of noise type clock is used to determine the clock bias prediction method; Finally, positioning experiment of the atomic clock and barometric altimeter aided BDS in simulation challenge environment is carried out, and the positioning result is analyzed. The results show that BDS can positioning solution to track two visible satellites, and vertical positioning accuracy is significantly improved. The positioning error in the vertical direction is decreased from 8.2 m (RMSE) to 5.2 m, and the fluctuation of the positioning results decreased from 4.6 m to 0.8 m.
Ship Azimuthal Speed Estimation Method Based on Local Region Doppler Centroid in SAR Images
Xiangfei WEI, Xiaoqing WANG, Jinsong CHONG
, doi: 10.11999/JEIT170991
[Abstract](40) [FullText HTML](9) [PDF 2209KB](2)
To deal with the problem that most of the existing ship speed estimation algorithms can only estimate the slant range speeds of ships, a ship azimuthal speed estimation method based on local region Doppler centroid for Synthetic Aperture Radar (SAR) images is proposed. Firstly, the variation of Doppler centroid of moving target in local region of SAR image is analyzed and the theoretical formula for estimating the azimuthal speed using the slope of Doppler centroid variation is derived. Then, based on the probability density function of azimuthal power spectrum, an estimation method for the slope of Doppler centroid variation using the maximum likelihood estimation algorithm is presented. Moreover, the estimation accuracy and the applicability of the proposed method are also analyzed. Finally, the proposed method is implemented on simulated and filed data and the estimation results are compared with those obtained by directly calculating the frequency modulation rate. The results show that the proposed method has high estimation accuracy, which verifies the effectiveness of the proposed method.
Anti-interrupted Sampling Repeater Jamming Waveform Design Method
Chang ZHOU, Ziyue TANG, Zhenbo ZHU, Yuanpeng ZHANG
, doi: 10.11999/JEIT171236
[Abstract](69) [FullText HTML](7) [PDF 2009KB](0)
Interrupted Sampling Repeater Jamming (ISRJ) is an advanced intensive false-target jamming with the advantages of fast interference response, anti-agile ability and so on. The radar signal is intermittently sampled with low-rate based on the principle of the under-sampling method, so that the radar can not detect the real targets and the jamming may overload the signal processing system. This article mainly focuses on the Interrupted Sampling Repeater Jamming. A sensitive Doppler sparse waveform is designed based on the ambiguity function theory to suppress the interference, which destroys the continuity of the interference signal output on different Doppler and suppresses the output of the intensive interference. Based on the analysis of the equivalent interval sidelobe, a method of sliding window extraction detection is proposed to achieve effective target detection while anti-jamming. Theoretical analysis and simulation experiments demonstrate the effectiveness of the interference suppression and the target detection performance in the interference.
Adaptive Grid Multiple Sources Localization Based on Sparse Bayesian Learning
Kangyong YOU, Lishan YANG, Yueliang LIU, Wenbin GUO, Wenbo WANG
, doi: 10.11999/JEIT171238
[Abstract](13) [FullText HTML](11) [PDF 1383KB](2)
Multiple sources localization is an issue of theoretical importance and practical significance in signal processing. The basis mismatch problem caused by target deviation from the initial grid point is addressed. Based on sparse Bayesian learning framework with Laplace prior, a novel iterative Adaptive Grid Multiple Targets Localization (AGMTL) algorithm is proposed to tackle the practical situation in which the targets deviates from the initial grid point. In essence, AGMTL algorithm implements sparse signal reconstruction and adaptive grid localization dictionary learning jointly. The simulation results show that AGMTL algorithm outperforms the traditional Compressive Sensing (CS) based localization algorithm in the terms of localization error, estimation reliability and noise robustness.
Independent Vector Analysis Convolutive Blind Separation Algorithm Based on Step-size Adaptive
Weihong FU, Cong ZHANG
, doi: 10.11999/JEIT171156
[Abstract](130) [FullText HTML](62) [PDF 1219KB](9)
Independent Vector Analysis (IVA) is one of the best methods to solve the sort ambiguity of convolutive blind separation in frequency domain. However, it needs more iterations and computing time, and the separation effect is susceptible to the initial value of the separation matrix. This paper proposes an IVA convolutive blind separation algorithm based on step-size adaptive, which uses Joint Approximative Diagonalization of Eigenmatrices (JADE) algorithm to initialize the separation matrix and optimizes adaptively the step step-size parameters. JADE initialization can make the separation matrix have an appropriate initial value, thus avoiding the situation of local convergence; step-size adaptive optimization can significantly improve the convergence speed of the algorithm. Simulation results show that this algorithm improves the separation performance and shortens the operation time significantly.
An Improved Algorithm of Product of Experts System Based on Restricted Boltzmann Machine
Huihui SHEN, Hongwei LI
, doi: 10.11999/JEIT170880
[Abstract](51) [FullText HTML](6) [PDF 2019KB](0)
Deep learning has a strong ability in the high-dimensional feature vector information extraction and classification. But the training time of deep learning is so long that the optimal hyper-parameters combination can not be found in a short time. To solve these problems, a method of product of experts system based on Restricted Boltzmann Machine (RBM) is proposed. The product of experts theory is combined with the RBM algorithm and the parameter updating way is all adopted the probability value, which leads to the undesirable recognition effect and slightly worse density models, so the parameter updating way is improved. An improved algorithm with momentum terms in different combinations is used not only in the RBM pre-training phase but also in the fine-tuning stage for both classification accuracy enhancement and training time decreasing. Through the recognition experiments on the MNIST database and CMU-PIE face database, the proposed algorithm reduces the training time, and improves the efficiency of hyper-parameters optimization, and then the deep belief network can achieve better classification performance. The result shows that the improved algorithm can improve both accuracy and computation efficiency in dealing with high-dimensional and large amounts of data, the new method is effective.
Interactive Genetic Algorithm Based on Collective Decision Making with Multi-user Collaboration
Guangsong GUO, Zhenhua WEN, Guosheng HAO
, doi: 10.11999/JEIT171234
[Abstract](59) [FullText HTML](7) [PDF 1054KB](0)
When using interactive genetic algorithm to solve big data information retrieval problem, single user needs to complete more human-machine interactive operation to achieve preference information extraction and optimization, thus it is easy to generate the problem of user fatigue and algorithm low efficiency. A multi-user strategy is introduced by making full use of the advantages of group decision to improve the sample utilization efficiency. First of all, multi-user collaborative type is devided into common collaboration or personalized collaboration according to the optimization goal which calculats user similarity and individual similarity based on user’s browsing behaviors. Then, individuals’ interval fitness is forecasted by sharing similar individual of similarity users. Based on phenotype similarity clustering, the large scale population individuals of " interval-interval” fitness assignment strategy is introduced. Finally, the best evaluation individual is recommended according to the similarities between offspring individuals and parent individuals. The proposed method is applied to decorative wallpaper design problem and is compared with existing typical methods. The experimental results confirm that the proposed algorithm has advantages in improving optimization quality and alleviating user fatigue while improving its efficiency in exploration.
Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes
Kai ZHANG, Yao TIAN, Yunpeng XIE, Yi LIU
, doi: 10.11999/JEIT180073
[Abstract](12) [FullText HTML](6) [PDF 2242KB](0)
For the issue of joint parameter estimation and symbol detection for multi-antenna signals with channel parameters difference over flat-fading channels, a new joint processing scheme is proposed based on the Variational Bayes (VB) method. The proposed scheme uses directly multiple received signals for the estimation of information symbols, restraining the information loss in conventional decoupled scheme of signals combination and demodulation. The problem is modeled as the joint Maximum A Posteriori (MAP) estimation of information symbols, time-delays, complex channel gains, and noise powers, given multiple observations, and approximately solved by means of VB approach. Based on the criterion of minimum relative entropy, analytical-form of the approximate distributions, i.e., variational distributions, for all unknown parameters are derived. There is no need to determine accurate point estimates of the parameters. Instead, the proposed scheme proceeds iteratively by alternating between the variational distributions of channel parameters and the information symbols. Simulation results show that the proposed joint processing scheme has significant performance improvements in comparison with conventional decoupled or partly joint processing schemes especially with large array sizes and short signal lengths.
Adaptive Sensor Scheduling Algorithm for Target Tracking in Wireless Sensor Networks
Bo HU, Qiyao WANG, Hui FENG, Lingbing LUO
, doi: 10.11999/JEIT171154
[Abstract](84) [FullText HTML](7) [PDF 1234KB](0)
In the process of target tracking, the sensor scheduling algorithm can achieve the tradeoff between the tracking error and the energy consumption so as to extend the service life of the sensor network. The issue can be modeled as a Partially Observable Markov Decision Process (POMDP), which takes both short- and long- term losses of sensor scheduling into account and makes a better decision. A C-QMDP approximation algorithm suitable for continuous state space is proposed. The Markov Chain Monte Carlo (MCMC) method is used to derive the transfer function of belief state and calculate the instantaneous cost. The state discretization method is used to solve the approximation of future cost based on Markov Decision Process (MDP) iteration. Simulation results show that compared to the existing POMDP approximation algorithms, the proposed algorithm can reduce the cumulative losses and computation load in the tracking process by offline computation.

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Satellite Platform Jitter Detection and Image Geometric Quality Compensation Based on High-frequency Angular Displacement Data
HU Kun, HUANG Xu, ZHANG Yongjun, YOU Hongjian
2018, 40(7): 1525-1531.   doi: 10.11999/JEIT170990
[Abstract](7) [PDF 0KB](2)
With the improvement of imaging resolution and on-orbit mobility of earth observation satellites, the imaging geometric quality is more apparently influenced by the attitude’s high-frequency jittering of satellite platform. The traditional time-division imaging data based jitter detection and compensation methods have many drawbacks, which include large amount of calculation and high degree of error interference in dense matching, and it is unable to decompose the jitter quantity in each rotation angle direction. This paper takes the high-frequency angular displacement equipment which is carried by China’s remote sensing optical satellite for example, studies on the direct jitter detection method and the image geometric quality compensation method based on high-frequency attitude measurement angular displacement data, which include the windowed FIR filter pre-processing of angular displacement data, the phase distribution analysis on time-dependent jitter curve in pitch, roll and yaw directions, as well as image direct positioning compensation based on angular displacement data. The high-frequency jitter compensation is applied to attitude recovery and geometric rectification based on strict imaging geometric model.The experimental results of China’ remote sensing satellite images in Beijing area illustrate that the methods proposed in this paper can significantly improve the accuracy and reliability of the high- frequency jitter detection, and can effectively improve the internal geometric quality of satellite image after jitter compensation. For example, the length deformation accuracy can be improved by 0.5 pixel.
Three Dimensional Path Planning of UAV with Improved Ant Lion Optimizer
HUANG Changqiang, ZHAO Kexin
2018, 40(7): 1532-1538.   doi: 10.11999/JEIT170961
[Abstract](6) [PDF 0KB](0)
Unmanned Aerial Vehicle (UAV) 3D path planning is the most complex and important part of mission planning. Considering at the problem that the problem of 3D path planning can not be solved by the original algorithm perfectly, so firstly the chaotic adjustment factor and anti-regulation factor are introduced into the behavior of ant and ant lion respectively, which improves the exploration and the exploitation of algorithm. Then, in order to reduce search space ,so terrain and constraints  are full used on the basis of the establishment of 3D environment model. Lastly, the improved algorithm is applied to the 3D path planning, which is compared with the original algorithm, and online local re-planning is implemented. Simulation results demonstrate the feasibility and superiority of the improved method.
Research on Detection Methods to Periodic Pulsed Interference for L Band Microwave Radiometer in Time Domain
JIANG Tao, ZHAO Kai, WAN Xiangkun
2018, 40(7): 1539-1545.   doi: 10.11999/JEIT170954
[Abstract](6) [PDF 0KB](0)
L-band passive microwave remote sensing is an effective method for detection of soil moisture and ocean salinity. However, spectrum pollution from Global Positioning System (GPS), radar and electromagnetic radiation from some commercial electronic products can interfere with the detection of microwave radiometers, it results in a certain deviation to the ground observation, and reduces the retrieval accuracy of the surface parameters. Pulsed noise interference is simulated by experiment, its transmission characteristics in L-band (total power receiver) microwave radiometer system is observed, the correlation between the characteristics of the output signal and the radiometer parameters (integrating time and sensitivity) is analyzed, its digital characteristic parameters are obtained. Combining the method of Asynchronous Pulse Blanking (APB), a new AutoCorrelation Detection (ACD) algorithm is proposed, which can detect periodic pulsed radiation interference effectively. In the case that microwave radiometer system integrating time is 1 ms, it can detect the noise interference of 1.5 K, which meets the requirement of precision of surface parameters retrieved by satellite remote sensing.
Target Point Tracks Association and Error Correction with Optical Satellite in Geostationary Orbit and Automatic Identification System
LIU Yong, YAO Libo, WU Yuzhou, XIU Jianjuan, ZHOU Zhimin
2018, 40(7): 1546-1552.   doi: 10.11999/JEIT170896
[Abstract](3) [PDF 0KB](0)
When ship target is monitored by the geostationary optical satellite, the positioning error is large due to the long distance between the target and the satellite, which affects the accuracy of the follow-up target tracking. As the monitoring area is mainly the ocean, it may not be possible to find the Ground Control Point (GCP) for coordinate correction. In order to improve the positioning accuracy of the geostationary optical satellite for ship without GCP, and to realize the fusion of multi-source data, a novel target point association and error correction with optical satellite in geostationary orbit and ship Automatic Identification System (AIS) is proposed. By means of the Rational Polynomial Coefficient (RPC) model, AIS coordinates are transformed into image coordinates. The Iterative Closest Point (ICP) and Global Nearest Neighbor (GNN) algorithm are combined and used for data association. Then, the error is corrected using the point pair of association. Experimental results using GF-4 images and AIS data verify the feasibility of the proposed method and show that the association algorithm has a high correlation rate, and the average positioning accuracy after error correction is improved greatly compared with the positioning accuracy before correction.
Equivalent Simulation Method for Pulse Radar ISAR Imaging in Radio Frequency Simulation
LIU Xiaobin, LIU Jin, LIU Guangjun, ZHAO Feng, WANG Guoyu
2018, 40(7): 1553-1560.   doi: 10.11999/JEIT170931
[Abstract](3) [PDF 0KB](0)
Pulse radar signal is widely used in Inverse Synthetic Aperture Radar (ISAR) imaging. However, because the propagation distance obtained by the pulse width is larger than the size of anechoic chamber, target echo returns before the pulse signal is fully transmitted. As a result, the transmitted and reflected signals are coupled and difficult to be separated for ISAR imaging in Radio Frequency Simulation (RFS). To solve this problem, the equivalent simulation method is proposed for pulse radar ISAR imaging based on Interrupted Transmitting and Receiving (ITR). As the ITR echo is piecewise sparse in time domain, the ISAR image can be reconstructed based on Compressive Sensing (CS). Simulation and real data demonstrate that the ISAR image obtained by the proposed method is consistent with that obtained by the complete pulse radar signal. Therefore, the proposed method is effective for ISAR imaging in RFS.
Robust Channel Mismatch Estimation in Multichannel HRWS SAR Based on Range Spectrum Analysis
FANG Chao, LIU Yanyang, SUO Zhiyong, LI Zhenfang, CHEN Junli
2018, 40(7): 1561-1566.   doi: 10.11999/JEIT170996
[Abstract](5) [PDF 0KB](0)
In multichannel High-Resolution and Wide-Swath (HRWS) Synthetic Aperture Radar (SAR) systems, channel amplitude and phase mismatches would degrade the performance of azimuth ambiguity suppression as well as range sampling mismatches. To address this problem, a robust estimation method based on range spectrum analysis is proposed in this letter. The method includes two steps: firstly, by exploiting the interferometric phases between the range spectrums of adjacent channels, the proposed method can robustly estimate range sampling mismatches by the combination of phase unwrapping and a weighted least squares fitting. Secondly, based on the theory of spatial cross correlation, an accurate Doppler centroid and phase mismatches could be obtained from constant phases between adjacent channels. Compared with traditional methods, the proposed method overcomes the effect of phase wraps and jumps on polynomial coefficient estimation. It not only improves the robustness of parameter estimation but also can simultaneously obtain the Doppler centroid and phase mismatches. Experimental results based on airborne real data and simulated data validate its effectiveness of the proposed method.
Recognition of Pulse Repetition Interval of Multilayer Percetron Network Based on Multi-parameter TDOA Sorting
CHEN Tao, WANG Tianhang, GUO Limin
2018, 40(7): 1567-1574.   doi: 10.11999/JEIT170913
[Abstract](3) [PDF 0KB](0)
In modern warfare, the radar system is developing rapidly. To recognize complex modulation mode of radar signal and hybrid pulse repetition interval radar, this paper proposes a sorting method based on multi station acquired pulse time-difference parameter combined with other pulse description words, taking advantage of the multi-station TDOA from the same emitter is similar to sort emitter signal pulse, and finally got the recognition result with the Multi-Layer Percetron (MLP) neural network. Traditional Pulse Repetition Interval (PRI) estimation algorithms estimate complex pulse interval modulation invalidly. In this paper, to solve this problem pulse time-difference parameter and other pulse description words are used. The feature vector of de-interlace pulse sequence is acquired and the result of pulse interval modulation type recognition is obtained with the trained MLP neutral network. Through experimental simulation, the correct recognition probability of the complex pulse interval modulation method is more than 90% in the case of the pulse loss rate is not more than 20%.
Range Scaling Compensation Method Based on STOLT Interpolation in Broadband Squint SAS Imaging
WANG Jinbo, TANG Jinsong, ZHANG Sen, ZHONG Heping
2018, 40(7): 1575-1582.   doi: 10.11999/JEIT171068
[Abstract](3) [PDF 0KB](0)
Considering the problem of large squint synthetic aperture sonar imaging, the analytical expression of the wavenumber spectrum is analyzed in detail in the radial and azimuth wavenumber fields under the wide-band high-squint conditions. The spectrum winding and shrink in the distance wavenumber fields after the Stolt interpolation are pointed out, and the reduced relative distance between the target in the imaging result is also indicated, then the Stolt interpolation method for distance wavenumber spectrum winding is given. The concept of range wavenumber scaling factor is proposed, the method of compensating the scaling factor and the spectrum winding in the distance space are given. Finally, the problem of range scaling caused by Stolt interpolation under large oblique angle is solved by compensating the distance variable in distance space. Point object simulation data and simulated echo data processing verify the correctness and validity of the proposed method.
Variational Bayesian-interacting Multiple Model Tracking Filter with Angle Glint Noise
XU Hong, YUAN Huadong, XIE Wenchong, LIU Weijian, WANG Yongliang
2018, 40(7): 1583-1590.   doi: 10.11999/JEIT171025
[Abstract](3) [PDF 0KB](0)
Research on target tracking with glint noise is important to improve detection performance of sensor, in which the glint noise’s unknown distribution and non-stationary property puzzle researchers for a long time. In order to solve this problem, the tracking theoretical framework of variational Bayesian parameter learning with glint noise is firstly introduced. Then, a novel algorithm called Variational Bayesian-Interacting Multiple Model (VB-IMM) is proposed to estimate the system states as well as the unknown glint noise’s distribution. The proposed algorithm designs a bank of tracking filters in parallel with different measurement noise. Moreover, the algorithm utilizes variational Bayesian method to learn distribution parameters of the glint noise online and feed these parameters back to the tracking filters to revise the filters. In order to validate the performance of this algorithm, comparative experiments are carried out from two aspects of tracking accuracy and computational complexity. Simulation results verify good performance of tracking error and low computational complexity of the proposed algorithm.
Time Difference of Arrival Passive Location Based on Salp Swarm Algorithm
CHEN Tao, WANG Mengxin, HUANG Xiangsong
2018, 40(7): 1591-1597.   doi: 10.11999/JEIT170979
[Abstract](4) [PDF 0KB](0)
To solve the nonlinear equation problems of Time-Difference-Of-Arrival (TDOA) passive location, a new swarm intelligence optimization algorithm called Salp-Swarm-Algorithm (SSA) is used. Firstly, a new renewal model of salps is proposed to balance exploration and exploitation properly during iteration in SSA. SSA not only ensures the wholeness of searching and the diversity of individuals, but also improves the problem that other intelligent optimization algorithms fall into local optima easily. Besides, there are few parameters to be adjusted, therefor, the computation speed is obviously improved. Moreover, the convergence performance of the proposed algorithm is very stable and the accuracy of location is higher. Simulation results show that the proposed algorithm can converge to the position of emitters fast and stably in 3D TDOA location. Comparing with Particle-Swarm- Optimization (PSO) and Improved-Particle-Swarm-Optimization (IPSO), the proposed algorithm has lower mean square error.
Symbol Rate Estimation Based on Sparse Bayesian Learning
JIN Yan, TIAN Tian, JI Hongbing
2018, 40(7): 1598-1603.   doi: 10.11999/JEIT170906
[Abstract](3) [PDF 0KB](0)
Existing methods for symbol rate estimation of phase coded signals require amounts of sensing data, and are of high computational complexity. This paper analyzes the structure characteristics of BPSK signals, which are employed as the prior information for signal compressing and dimensionality reduction. The sensing matrix can be split into sine and cosine component, combined with the Fourier transform parity. According to the fact that the real and imaginary components of a complex value share the same support set, the symbol rate estimation can be obtained, using unilateral spectral of the delay-product vector reconstructed by multi-task Bayesian compressive sensing. Theoretical analysis and simulation results show that compared with other parameter estimation algorithms, the proposed method can reduce the measurements and significantly improve the real-time ability, while keeping the high reconstruction accuracy.
DOA Estimation for Co-prime Array Based on Fast Sparse Bayesian Learning Using Bessel Priors
FENG Mingyue, HE Minghao, CHEN Changxiao, HAN Jun
2018, 40(7): 1604-1611.   doi: 10.11999/JEIT170951
[Abstract](4) [PDF 0KB](0)
In order to improve DOA estimation accuracy of co-prime array while the number of snapshots is small, a novel fast Sparse Bayesian Learning (SBL) algorithm using Bessel priors is proposed. Focusing on the multi-snapshots complex output data of coprime array, a multiple measurement vectors hierarchical model based on Bessel priors is firstly built. Then the log-likelihood function of model hyperparameters is derived, and the iterative formulas of hyperparameters are derived based on the criterion of maximum likelihood estimation. Finally, a fast implementation scheme is developed in order to improve the computation efficiency. Simulation experiments show that the proposed algorithm is independent on prior information. Under the condition of small number of snapshots, higher DOA estimation accuracy and resolution of uncorrelated and correlated signals can be achieved with proper computational efficiency. Further more, the necessity between virtual array extension and DOA estimation freedom of co-prime array is explored, which provides reference to DOA estimation for co-prime array under array perturbation conditions.
Teager Energy Operator and Empirical Mode Decomposition Based Voice Activity Detection Method
SHEN Xizhong, ZHENG Xiaoxiu
2018, 40(7): 1612-1618.   doi: 10.11999/JEIT171014
[Abstract](3) [PDF 0KB](0)
In recent years, Teager energy operator is proposed as a kind of nonlinear method characterized with tracking a time-varying signal. The operator is combined with empirical mode decomposition, and a new method of voice activity detection is proposed to find the best voice start point and end point. Empirical Mode Decomposition (EMD) is further exploited and some valid choice conditions are constructed to choose the valid intrinsic mode functions. Thus, the method is able to deal with the voice with noise. Also, the character of the single mode of empirical mode decomposition meets the demand of single frequency component required by Teager Energy Operator (TEO). At last, Hilbert transform is added to solve the inherent problem of the mode mixing due to empirical mode decomposition. Based on the above consideration, the proposed method can identify the unvoiced sound with noise, which is better than the direct TEO and double threshold method. Experiments show the validity of the proposed method.
Canonical Correlation Analysis Based Sparse Representation Model for Robust Visual Tracking
KANG Bin, CAO Wenwen, YAN Jun, ZHANG Suofei
2018, 40(7): 1619-1626.   doi: 10.11999/JEIT170939
[Abstract](6) [PDF 0KB](0)
In traditional sparse representation based visual tracking, particle sampling is first achieved by particle filter method. Then the particle observations are represented by intensity feature. Finally, the visual tracking is achieved by the intensity feature based sparse representation model. Different from traditional sparse representation model, a canonical correlation analysis based sparse representation model is proposed in this paper. The proposed model first uses two kinds of features to represent the particle observations, then, the projections of particle observations are used to build the sparse representation model. The advantage of the proposed model lies in that it can give a proper multi-feature fusing through canonical correlation analysis, which explores the relation between two features in a latent common subspace.
Research and Implementation on Flower Plants Rendering Technology Based on Physical Light Simulation for VR Application
HUAI Yongjian, ZHANG Han, ZHANG Shuai
2018, 40(7): 1627-1634.   doi: 10.11999/JEIJ170995
[Abstract](6) [PDF 0KB](0)
The high realism simulation interaction of flower plants is an important direction of virtual plant visualization. More and more applications are presented by the Virtual Reality (VR) headset device with the popularity of virtual reality technology. The VR system requires a highly realistic immersive picture for which generic plant modeling and graphics engine rendering capabilities are no longer sufficient. In this paper, a physical rendering algorithm is proposed based on Bidirectional Scattering Distribution Function (BSDF) to realistic flower plants by analyzing the principle of illumination and combining the Physics-Based Shading (PBS) technology. Potted flora in light mode is simulated by ShaderLab and the fusion algorithm is optimized. The image is distorted by lens matching rendering technology to make the virtual scene closer to the real human eye vision and reduce the user vertigo when user wearing the VR headset when using the VR helmet equipment HTC Vive. Finally a helmet VR floral plant simulation system is designed and a realistic immersive scene is realized.
Efficient Audio-visual Cross-modal Speaker Tagging via Supervised Joint Correspondence Auto-encoder
LIU Xin, LI Heyang, ZHONG Bineng, DU Jixiang
2018, 40(7): 1635-1642.   doi: 10.11999/JEIT171011
[Abstract](5) [PDF 0KB](0)
Cross-modal speaker tagging aims to learn the latent relationship between different biometrics for mutual annotation, which can potentially be utilized in various human-computer interactions. In order to solve the “semantic gap” between the face and audio modalities, this paper presents an efficient supervised joint correspondence auto-encoder to link the face and audio counterpart, where by the speaker can be crosswise tagged. First, Convolutional Neural Network (CNN) and Deep Belief Network (DBN) are used to extract the discriminative features of the face and the audio samples respectively. Then, a supervised neural network model associated with softmax regression is embedded into a joint auto-encoder model, which can discriminatively preserving the inter-modal and intra-modal similarities. Accordingly, three different kinds of supervised joint correspondence auto-encoder models are presented to correlate the semantic relationships between the face and the audio counterparts, and the speaker can be crosswise annotated efficiently. The experimental results show that the proposed supervised joint auto-encoder is able to perform cross-modal speaker tagging with outstanding performance, and demonstrate the robustness to facial posture variations and sample diversities.
Improved Binary Glowworm Swarm Optimization Combined with Complementarity Measure for Ensemble Pruning
ZHU Xuhui, NI Zhiwei, NI Liping, JIN Feifei, CHENG Meiying, LI Jingming
2018, 40(7): 1643-1651.   doi: 10.11999/JEIT170984
[Abstract](2) [PDF 0KB](0)
The key to the success of an ensemble system are the diversity and the average accuracy of base classifiers. The increase of diversity among base classifiers will lead to the decrease of the average accuracy, and vice versa. So there exists a tradeoff between the diversity and the average accuracy, which makes the ensemble perform the best with respect to ensemble pruning. To find the tradeoff, Improved Binary Glowworm Swarm Optimization combined with Complementarity measure for Ensemble Pruning (IBGSOCEP) is proposed. Firstly, an initial pool of classifiers is constructed through training independently some base classifiers using bootstrap sampling. Secondly, the classifiers in the initial pool are pre-pruned using complementarity measure. Thirdly, Improved Binary Glowworm Swarm Optimization (IBGSO) is proposed by improving moving way, searching processes of glowworm, introducing re-initialization, and leaping behaviors. Finally, the optimal sub-ensemble is achieved from the base classifiers after pre-pruning using IBGSO. Experimental results on 5 UCI datasets demonstrate that IBGSODSEN can achieve better results than other approaches with less number of base classifiers, and that its effectiveness and significance.
An Efficient Ciphertext-policy Attribute-based Encryption on Ideal Lattices
ZHAO Jian, GAO Haiying, HU Bin
2018, 40(7): 1652-1660.   doi: 10.11999/JEIT170863
[Abstract](3) [PDF 0KB](0)
The existing Ciphertext-Policy Attribute-Based Encryption (CP-ABE) schemes from lattices are inefficient while they are performed in matrix operation, and these Key-Policy Attribute-Based Encryption (KP-ABE) schemes from ideal lattices with higher efficiency are inadaptable to most practical application scenarios. To solve these problems, the new scheme generates master keys and secret keys by the algorithms based on ideal lattices and the whole scheme is computed over a polynomial ring, thus its efficiency of encryption and decryption can be greatly improved. The ciphertexts associated with access structure are successfully generated by adding some virtual attributes to the original attribute set. Meanwhile, the authorized user can build a subset based on these virtual attributes for decrypting the scheme correctly. And the secret keys are generated by a single trapdoor matrix, which reduces the number of public parameters and master keys effectively. Finally, an efficient CP-ABE scheme for flexible threshold access structures on ideal lattices is proposed, and its security is reduced to decisional Learning With Errors over Ring (R-LWE) assumption against chosen plaintext attack in the selective security model. Comparative analysis of similar schemes shows that the new scheme has less public parameters and higher efficiency, and gets better adaptability to the practical application scenarios.
Expressive Ciphertext-policy Attribute-based Encryption Scheme with Fast Decryption and Constant-size Secret Keys
LI Long, GU Tianlong, CHANG Liang, XU Zhoubo, QIAN Junyan
2018, 40(7): 1661-1668.   doi: 10.11999/JEIT171086
[Abstract](5) [PDF 0KB](0)
Under the premise of ensuring the security of Ciphertext-Policy Attribute Based Encryption (CP-ABE), to enhance efficiency as much as possible is always a research hotspot in the field of cryptography. Starting from the access structure, which is the efficiency basis of CP-ABE, a new kind of access structure is proposed based on Reduced Ordered Binary Decision Diagrams (ROBDD) for the first time, and the corresponding strategy representation method and satisfaction determination are given. Furthermore, based on the above access structure, a new CP-ABE with good performance in lots of aspects, such as time complexity of algorithms and storage occupancy of secret keys, is designed; In terms of security, the scheme can resist collusion attack and chosen plaintext attack. Comparative analysis shows that, ROBDD access structure has stronger expression ability and higher expression efficiency; In the new CP-ABE scheme, the time complexity of key generation algorithm and decryption algorithm is O(1), which can generate constant-size secret keys and achieve fast decryption.
Analysis of Constructing Fully Homomorphic Encryption Based on the Abstract Decryption Structure
SONG Xinxia, CHEN Zhigang
2018, 40(7): 1669-1675.   doi: 10.11999/JEIT170997
[Abstract](2) [PDF 0KB](0)
Why can fully homomorphic encryption be constructed based on lattice What is the essence and construction of the matrix  An important concept is proposed: Abstract decryption structure. Based on the abstract decryption structure, the main factors related to the homomorphic encryption are analyzed and relationship between abstract decryption structure, homomorphism and noise control is studied. The construction of the homomorphic encryption is attributed to the problem of how to obtain the final decryption structure. So the formal method of homomorphic encryption can be established. Thus the essential law of the construction method of the homomorphic encryption construction is expounded, which provides the clue and clue for the construction of the new full homomorphic encryption. The general reason of the full homomorphic encryption of the ciphertext matrix from the point of view of the ciphertexts stack method is studied. The relation between the full homomorphic encryption and the other homomorphic encryption is obtained. Finally, this paper gives a general method of constructing fully homomorphic encryption.
Malicious Attack-resistant Secure Localization Algorithm for ZigBee Network
YU Bin, LIU Ziqing
2018, 40(7): 1676-1683.   doi: 10.11999/JEIT170962
[Abstract](5) [PDF 0KB](0)
A malicious attack-resistant secure localization algorithm Evolutionary Location Algorithm with the Maximum Probability value (ELAMP) based on evolutionism is proposed. According to the maximum likelihood estimation probability model and the distribution of Received Signal Strength (RSS) standard deviation and the distance, a secure location model of ZigBee network is established. Furthermore, the evolutionary algorithm is designed to solve the model, and the convergence and the time complexity of the algorithm is analyzed. Experimental results show that the proposed algorithm has better positioning accuracy than the existing positioning algorithm when the proportion of malicious nodes is not more than 50%.
A Virtual Network Embedding Algorithm Based on Topology Potential
LIU Xinbo, WANG Buhong, YANG Zhixian, LIU Shuaiqi
2018, 40(7): 1684-1690.   doi: 10.11999/JEIT170981
[Abstract](5) [PDF 0KB](0)
To improve the low acceptance ratio and revenue-cost ratio caused by the negligence of the topology attribute of the nodes in the existing virtual network embedding algorithm, the theory of fields in physics is introduced into the virtual network embedding, and a Virtual Network Embedding algorithm based on Topology Potential (TP-VNE) is proposed. In the node embedding stage, the virtual node is embedded onto the optimal physical node by calculating the topology potential of the node, the resource capacity of the node, and the distance between the embedded nodes and the node to embed. In the link embedding stage, the virtual link is embedded onto the best physical path by calculating the available bandwidth of the path and the hops of the path. Experimental results show that the proposed algorithm has the higher acceptance ratio and revenue-cost ratio compared with the existing virtual network embedding algorithm in all simulation conditions.
Delay Minimization Retransmission Scheme Based on Instantly Decodable Network Coding for D2D Communications
WANG Lian, WANG Meng, REN Zhihao, BAI Jiajie
2018, 40(7): 1691-1698.   doi: 10.11999/JEIT170976
[Abstract](3) [PDF 0KB](0)
A delay minimization retransmission scheme based on an instantly decodable network coding is proposed to solve the conflict problem when multiple devices cooperatively retransmit in Device-to-Device (D2D) wireless networks concurrently. In retransmission stage, making full use of multiple devices cooperative transmission advantages in D2D wireless network, combined with the packet receiving state of each devices, taking all of the influence factors of delay into account, and then the packets with smaller incremental delay for each retransmission are selected to generate encoding packets to minimize the retransmission delay. At the same time, the devices conflict graph is constructed and the maximal independent set is searched in the graph. According to the encoding package weight value of each device, the maximum weighted independent set are selected as the concurrent cooperative retransmission devices to reduce the number of retransmission. Simulation results show that the proposed scheme can further improve the retransmission efficiency of D2D wireless network.
Online Task Allocation of Spatial Crowdsourcing Based on Dynamic Utility
YU Dunhui, ZHANG Lingli, FU Cong
2018, 40(7): 1699-1706.   doi: 10.11999/JEIT170930
[Abstract](3) [PDF 0KB](0)
In order to improve the overall effectiveness of the online assignment of crowdsourcing tasks, an online task assignment method is proposed for the space-time crowdsourcing environment. To deal with the problem of online task assignment in spatiotemporal crowdsourcing environment, a K-NearestNeighbor (KNN) algorithm is firstly proposed based on crowdsourcing task to select the candidate crowdsourcing workers. Then a threshold selection algorithm based on dynamic utility is designed to realize the optimal allocation of crowdsourcing workers and tasks. Experimental results show that the proposed algorithm is effective and feasible, and can guarantee the reliability of crowdsourcing workers and optimize the overall efficiency of the platform.
Information Propagation Control Method in Social Networks Based on Exact Controllability Theory
HUANG Hongcheng, LAI Licheng, HU Min, SUN Xinran, TAO Yang
2018, 40(7): 1707-1714.   doi: 10.11999/JEIT170966
[Abstract](4) [PDF 0KB](0)
In order to control the information propagation of the whole network at a lower cost, some information propagation control methods are introduced into social networks to select the best control point at a proper time. However, few work considers the weak ties between nodes to control the information propagation. Due to the characteristics of the complementation of information demand and the continuous assimilation of behavior orientation, the weak ties between nodes may be explosive in the process of information propagation, thus they can not be ignored. To solve this problem, considering the impact of strong and weak ties between nodes on information propagation, a propagation control method based on the exact controllability theory is proposed. Firstly, some strong ties between nodes, such as the node's intimacy, authority and interaction frequency are introduced to build the initial tie networks. Secondly, some potential valuable weak ties between nodes are identified and then tie networks are further updated. Finally, the exact controllability theory is used to find the driver node groups, and then the set of driver nodes are selected according to the characteristics of information propagation to control information propagation. Experimental results show that the proposed method can effectively promote or suppress the information propagation, which provides some ideas for the information propagation control in social networks.
Research of Network Capacity and Transmission Energy  Consumption in WSNs Based on Game Theory
HAO Xiaochen, LIU Jinshuo, YAO Ning, XIE Lixia, WANG Liyuan
2018, 40(7): 1715-1722.   doi: 10.11999/JEIT170927
[Abstract](3) [PDF 0KB](0)
To solve the problem that the network capacity decreases with the increasing interference in Wireless Sensor Networks (WSNs), a joint power control and channel allocation optimization game model is constructed, which considers the limitation of network energy. This game model contains the network capacity and the energy consumption of data transmission in the network. Theoretical analysis proves the existence of the optimal power and the optimal channel. Based on the model, a joint Power control and Channel allocation Optimization Algorithm for wireless sensor networks (PCOA) is proposed, which adopts the best response strategy. The theoretical analysis proves that this algorithm can converge to Nash Equilibrium. Besides, the information complexity of this algorithm is small. Simulation results show that PCOA algorithm can reduce the interference and the energy consumption, which increases the network capacity.
Algorithm for Computing the k-error Linear Complexity and the Corresponding Error Sequence of 2pn-periodic Sequences over GF(q)
NIU Zhihua, KONG Deyu
2018, 40(7): 1723-1730.   doi: 10.11999/JEIT170972
[Abstract](2) [PDF 0KB](0)
The k-error linear complexity of a sequence is a fundamental concept for assessing the stability of the linear complexity. After computing the k-error linear complexity of a sequence, those bits that make the linear complexity reduced also need to be computed. For 2pn-periodic sequence over GF(q) , where p and q are odd primes and q is a primitive root modulo p2, an algorithm is presented, which not only computes the k-error linear complexity of a sequence s but also gets the corresponding error sequence e. A function is designed to trace the vector cost called “trace function”, so the error sequence e can be computed by calling the “trace function”, and the linear complexity of (s+e) reaches the k-error linear complexity of the sequence s.
Stochastic Programming and Buyer-seller Game Methods for Workload Distribution in an Ad-hoc Mobile Cloud
2018, 40(7): 1731-1737.   doi: 10:11999/JEIT170895
[Abstract](3) [PDF 0KB](0)
In order to solve the limitation of processing capacity and energy of single mobile equipment, the conception of Ad-hoc mobile cloud is proposed recently, in which a mobile device can use the idle resources at other neighboring devices for processing data and storage in Ad-hoc manner. To this end, this paper designs a workload distribution for offloading among mobile equipment. Considering the random and intermittent connections between mobile equipment caused by the movement in wireless network, a stochastic programming method is adopted to take posterior recourse actions to compensate for inaccurate predictions. Moreover, in order to motivate the available mobile equipment for offloading while maximizing their utilities, a distributed multi-stage Stochastic buyer/seller Game for Workload Distribution (SGWD) is formulated. Numerical results show the effectiveness of SGWD compared with the benchmark method in terms of communication cost, the delay, energy consumption and the payoff.
Resource Scheduling Mechanism for Virtual Network Slice Based on Online Double Auction
CHEN Qianbin, SHI Yingjie, YANG Xixi, TANG Lun
2018, 40(7): 1738-1744.   doi: 10.11999/JEIT170902
[Abstract](4) [PDF 0KB](0)
In order to solve the problem of resource allocation between 5G virtual network slice, a resource scheduling mechanism based on Online Double Auction (ODA) is proposed. Firstly, the priority of network slices and unit resource quotes are determined according to different traffic needs and traffic benefits. Then, to maximize the network revenue, an offline single auction model is established. Further, based on the resources dynamic allocation and recycling, the price-updating algorithm is proposed to update the resource price in real time. Finally, the offline single auction mechanism and the price update mechanism are combined to establish ODA model and allocate resources dynamically for the network slices. The simulation results show that the proposed mechanism can improve network revenue and guarantee the QoS requirement of each slice user.
Study on Tropospheric Scatter Beyond-line-of-sight Channel Transmission Loss for Short-term and Long-term Fading
WEI Peipei, DU Xiaoyan, JIANG Changyin
2018, 40(7): 1745-1751.   doi: 10.11999/JEIT170952
[Abstract](3) [PDF 0KB](0)
Tropospheric scatter (Troposcatter) communication is an important means for ground microwave beyond-line-of-sight propagation. Available troposcatter transmission loss models are inefficient to describe the random variables resulting from atmosphere environment and other factors. Therefore, this paper studies the short-term fading and long-term fading characteristics of transmission loss based on those of electric field strength for the first time. The distribution model of transmission loss is modeled, whose parameters are estimated referring to ITU-R P.617-3. Parts of measured scatter links data from International Telecommunication Union (ITU) are chosen to verify this model with normal distribution graph. The result shows that the long-term fading of transmission obeys the normal distribution. It gives the basis of calculating error bit for the further work. In addition, a transmission loss prediction method is proposed based on its distribution model. It is verified to have a good accuracy using measured data, and this method address the problem that available transmission loss methods can not predict the values at any time percentages.
Construction of Nearly Perfect Gaussian Integer Sequences
LI Yubo, CHEN Miao
2018, 40(7): 1752-1758.   doi: 10.11999/JEIT170844
[Abstract](3) [PDF 0KB](0)
A construction of Gaussian integer sequences based on pseudo-random sequences. Gaussian integer sequences with period  pm-1 whose degree p-1  are constructed from p-ary pseudo-random sequences with period pm-1. The presented sequences are nearly perfect Gaussian integer sequences with p-2 non-zero out-of-phase autocorrelation values. Moreover, these Gaussian integer sequences have balance property, as a result, they will be widely used in wireless communication and radar systems.
Fault-tolerant Last Level Cache Architecture Design at Near-threshold Voltage
LIU Wei, WEI Zhigang, DU Wei, CAO Guangyi, WANG Wei
2018, 40(7): 1759-1766.   doi: 10.11999/JEIT170989
[Abstract](1) [PDF 0KB](0)
Near-threshold voltage computing enables transistor voltage scaling to continue with Moore’s Law projection and dramatically improves power and energy efficiency. However, a great number of bit-cell errors occur in large SRAM structures, such as Last-Level Cache (LLC). A Fault-Tolerant LLC (FTLLC) design with conventional 6T SRAM cells is proposed to deal with a higher failure rate which is more than 1% at near-threshold voltage. FTLLC improves the reliability of data stored in Cache by correcting the single-error and compressing multi-errors in Cache entry. To validate the efficiency of FTLLC, FTLLC and prior works are implemented in gem5, and are simulated with SPEC CPU2006. The experiment shows that compared with Concertina at 650 mV, the performance of a 65 nm FTLLC with 4-Byte subblock size improves by 7.2% and the Cache capacity increases by 24.9%. Besides, the miss rate decreases by 58.2%, and there are little increases on area overhead and power consumption.
Investigation of Quasi-optical Mode Converter for W Band Gyrotron
ZHAO Guohui, XUE Qianzhong, WANG Yong, WANG Hu, GENG Zhihui, ZHANG Shan, WANG Xuewei
2018, 40(7): 1767-1773.   doi: 10.11999/JEIT170998
[Abstract](1) [PDF 0KB](0)
The design and experimental verification of the launcher and mirror system of W band TE62 mode gyrotron quasi optical mode converter are presented. Based on the coupled mode theory, two order perturbation is used to design the launcher. The field distribution of the Gauss beam spot on the inner wall of the circular waveguide is obtained. The vector diffraction integral theory based on Huygens,s principle is used to optimize the mirror system of the optical mode converter. Simulation and calculation results show that the mode conversion efficiency of quasi optical mode the converter is 92.3%. Finally, a thermal measurement experiment is carried out to verify that the output mode is W band Gauss like mode.
Cognitive Radar Waveform Design with A Peak to Average Power Ration Constraint for Spectrally Dense Environments
ZOU Kun, LUO Yanbo, LI Wei, LI Hailin
2018, 40(7): 1774-1778.   doi: 10.11999/JEIT170834
[Abstract](2) [PDF 0KB](0)
The most important characteristic of the complex electromagnetic environment is the limitation of the radio frequency resource. As a result, the smart use of the limiting spectral resource is necessary to the waveform design for the cognitive radar. This paper designs the transmit waveform under the Peak to Average power Ratio (PAR), to maximize the Signal to Noise power Ratio (SNR) at the receiver, and simultaneously, minimize the power of the waveform in the interference frequency bands. The waveform design problem is a quadratically constrained multi-objective optimization problem. Exploiting the Pareto optimization method, the one objective function is obtained by weighted sum of the two ones, and the resultant problem reduces into a Quadratically Constrained Quadratic Program (QCQP). In order to solve it, the SemiDefinite Program (SDP) relaxation and randomization are used to achieve the optimal waveform, whose performance is related to the Pareto weights and the PAR constraint. The computer simulation results show that, there is a restrictive relationship between the SNR and interference suppression ability for the waveform design, and the performance can be improved by increasing the dynamic range of the transmitter.

Monthly Journal Founded in 1979

The Source Journal of EI Compendex The Source Journal of ESCI Database

Competent unit:Authorized by CAS

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Editor-in-Chief:Yirong Wu

ISSN 1009-5896  CN 11-4494/TN

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