高级搜索

基于多点协作联合传输的超密集组网性能分析

曾孝平 余丰 简鑫 李诗琪 杜得荣 蒋欣 方伟

引用本文: 曾孝平, 余丰, 简鑫, 李诗琪, 杜得荣, 蒋欣, 方伟. 基于多点协作联合传输的超密集组网性能分析[J]. 电子与信息学报, 2019, 41(3): 563-570. doi: 10.11999/JEIT180398 shu
Citation:  Xiaoping ZENG, Feng YU, Xin JIAN, Shiqi LI, Derong DU, Xin JIANG, Wei FANG. Performance Analysis of Ultra-dense Networks Based on Coordinated Multiple-points Joint Transmission[J]. Journal of Electronics and Information Technology, 2019, 41(3): 563-570. doi: 10.11999/JEIT180398 shu

基于多点协作联合传输的超密集组网性能分析

    作者简介: 曾孝平: 男,1956年生,教授,研究方向为下一代移动通信、无线通信、空间信息网;
    余丰: 女,1994年生,硕士生,研究方向为下一代移动通信、无线通信;
    简鑫: 男,1987年生,副教授,研究方向为下一代移动通信、多入多出网络;
    李诗琪: 女,1996年生,硕士生,研究方向为下一代移动通信、空间信息网;
    杜得荣: 男,1986年生,博士,研究方向为移动无线信道建模、空间信息网;
    蒋欣: 男,1970年生,博士,研究员,研究方向为航空电子系统综合设计技术和机载系统技术;
    方伟: 男,1978年生,博士,高级工程师,研究方向为航空电子系统、机载宽带通信技术等
    通讯作者: 曾孝平,zxp@cqu.edu.cn
  • 基金项目: 国家自然科学基金(61501065, 61571069, 61701054, 61601067),中央高校基本科研业务费(106112017CDJQJ168817),重庆市基础科学与前沿技术研究专项(cstc2016jcyjA0021)

摘要: 超密集组网的基站高密度特性会带来严重的小区间干扰,多点协作联合传输应用于超密集组网进行干扰管理是目前的研究热点,该文对多点协作联合传输时基站密度对网络性能的影响进行了分析。首先采用随机几何方法推导了3维空间基站与用户距离的概率密度函数,为选取距离用户最近的多个基站联合传输的协作机制提供了基础;然后结合有界双斜率路径损耗模型,进行用户下行链路的干扰建模,进一步推导出用户下行链路覆盖率和网络区域频谱效率的表达式,并分析了协作基站数、基站密度等参数对网络性能的影响。数值仿真表明:协作基站数为2时就可使下行链路覆盖率增加10%,且实现2到3倍的频谱效率的增益,当协作基站数为3时,费效比更优,同时可得到多点协作下的基站密度极限使区域频谱效率最高。该文工作可为下一代移动通信网络的基站部署提供理论支持。

English

    1. [1]

      LOPEZ-PEREZ D, DING Ming, CLAUSSEN H, et al. Towards 1 Gbps/UE in cellular systems: understanding ultra-dense small cell deployments[J]. IEEE Communications Surveys & Tutorials, 2015, 17(4): 2078–2101. doi: 10.1109/COMST.2015.2439636

    2. [2]

      ANANG K A, RPAJIC P B, ENEH T I, et al. Minimum cell size for information capacity increase in cellular wireless network[C]. IEEE Vehicular Technology Conference, Yokohama, Japan, 2011: 1–6.

    3. [3]

      GE Xiaohu, TU Song, MAO Guoqiang, et al. 5G ultra-dense cellular networks[J]. IEEE Wireless Communications, 2016, 23(1): 72–79. doi: 10.1109/MWC.2016.7422408

    4. [4]

      VAZE R and IYER S K. Capacity of cellular wireless network[C]. 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Paris, France, 2017: 1–8.

    5. [5]

      ANDREWS J G, ZHANG Xinchen, DURGIN G D, et al. Are we approaching the fundamental limits of wireless network densification?[J]. IEEE Communications Magazine, 2016, 54(10): 184–190. doi: 10.1109/MCOM.2016.7588290

    6. [6]

      ZHANG Xinchen and ANDREWS J G. Downlink cellular network analysis with multi-slope path loss models[J]. IEEE Transactions on Communications, 2015, 63(5): 1881–1894. doi: 10.1109/TCOMM.2015.2413412

    7. [7]

      GE Xiaohu, DU Bangzheng, LI Qiang, et al. Energy efficiency of multiuser multi-antenna random cellular networks with minimum distance constraints[J]. IEEE Transactions on Vehicular Technology, 2016, 66(2): 1696–1708. doi: 10.1109/TVT.2016.2557359

    8. [8]

      XU Ding, ZHANG Jianhua, GAO Xinying, et al. Indoor office propagation measurements and path loss models at 5.25 GHz[C]. IEEE Vehicular Technology Conference, Baltimore, USA, 2007: 844–848.

    9. [9]

      KORRAI P K and SEN D. Downlink SINR coverage and rate analysis with dual slope pathloss model in mmWave networks[C]. IEEE Wireless Communications and Networking Conference, San Francisco, USA, 2017: 1–6.

    10. [10]

      LIU Junyu, SHENG Min, LIU Lei, et al. Network densification in 5G: From the short-range communications perspective[J]. IEEE Communications Magazine, 2017, 55(12): 96–102. doi: 10.1109/MCOM.2017.1700487

    11. [11]

      ANDREWS J G, BACCELLI F, and GANTI R K. A tractable approach to coverage and rate in cellular networks[J]. IEEE Transactions on Communications, 2011, 59(11): 3122–3134. doi: 10.1109/TCOMM.2011.100411.100541

    12. [12]

      DING Ming, LOPEZ-PEREZ D, MAO Guoqiang, et al. Will the area spectral efficiency monotonically grow as small cells go dense?[C]. IEEE Global Communications Conference, San Diego, USA, 2015: 1–7.

    13. [13]

      LIU Junyu, SHENG Min, LIU Lei, et al. Effect of densification on cellular network performance with bounded pathloss model[J]. IEEE Communications Letters, 2017, 21(2): 346–349. doi: 10.1109/LCOMM.2016.2615298

    14. [14]

      ARNAU J, ATZENI I, and KOUNTOURIS M. Impact of LOS/NLOS propagation and path loss in ultra-dense cellular networks[C]. ICC 2016 IEEE International Conference on Communications, Kuala Lumpur, Malaysia, 2016: 1–6.

    15. [15]

      DING Ming, WANG Peng, LOPEZ-PEREZ D, et al. Performance impact of LoS and NLoS transmissions in dense cellular networks[J]. IEEE Transactions on Wireless Communications, 2015, 15(3): 2365–2380. doi: 10.1109/TWC.2015.2503391

    16. [16]

      NGUYEN V M and KOUNTOURIS M. Performance limits of network densification[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(6): 1294–1308. doi: 10.1109/JSAC.2017.2687638

    17. [17]

      YANG Yanpeng, PARK J, and SUNG K W. On the asymptotic behavior of ultra-densification under a bounded dual-slope path loss model[C]. To Appear in European Wireless, Dresden, Germany, 2017: 229–235.

    18. [18]

      GUPTA A K, ZHANG Xinchen, and ANDREWS J G. Potential throughput in 3D ultradense cellular networks[C]. Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2015: 1026–1030.

    19. [19]

      LI Qian, HU Qingyang, and QIAN Yi. Cooperative communications for wireless networks: Techniques and applications in LTE-advanced systems[J]. IEEE Wireless Communications, 2012, 19(2): 22–29. doi: 10.1109/MWC.2012.6189409

    20. [20]

      LIU Junyu, SHENG Min, LIU Lei, et al. Interference management in ultra-dense networks: Challenges and approaches[J]. IEEE Network, 2017, 31(6): 70–77. doi: 10.1109/MNET.2017.1700052

    21. [21]

      YANG Yanpeng, SUNG K W, PARK J, et al. Cooperative transmissions in ultra-dense networks under a bounded dual-slope path loss model[C]. European Conference on Networks and Communications, Oulu, Finland, 2017: 1–6.

    22. [22]

      朱晓荣, 朱蔚然. 超密集小蜂窝网中基于干扰协调的小区分簇和功率分配算法[J]. 电子与信息学报, 2016, 38(5): 1173–1178. doi: 10.11999/JEIT150756
      ZHU Xiaorong and ZHU Weiran. Interference coordination-based cell clustering and power allocation algorithm in dense small cell networks[J]. Journal of Electronics &Information Technology, 2016, 38(5): 1173–1178. doi: 10.11999/JEIT150756

    23. [23]

      BANANI S A and ADVE R S. Analyzing the reduced required BS density due to CoMP in cellular networks[C]. Global Communications Conference, Atlanta, USA, 2013: 2015–2019. doi: 10.1109/GLOCOM.2013.6831371.

    24. [24]

      BANANI S A and ADVE R S. The density penalty for random deployments in uplink CoMP networks[C]. Wireless Communications and Networking Conference, Istanbul, Turkey, 2014: 577–582. doi: 10.1109/WCNC.2014.6952092.

    25. [25]

      BACCELLI F and GIOVANIDIS A. A stochastic geometry framework for analyzing pairwise-cooperative cellular networks[J]. IEEE Transactions on Wireless Communications, 2014, 14(2): 794–808. doi: 10.1109/TWC.2014.2360196

    26. [26]

      HUANG Kaibin and ANDREWS J G. An analytical framework for multicell cooperation via stochastic geometry and large deviations[J]. IEEE Transactions on Information Theory, 2012, 59(4): 2501–2516. doi: 10.1109/TIT.2012.2232966

    27. [27]

      PAN Ziyu and ZHU Qi. Modeling and analysis of coverage in 3-D cellular networks[J]. IEEE Communications Letters, 2015, 19(5): 831–834. doi: 10.1109/LCOMM.2015.2411599

    28. [28]

      STREIT R L, 史习智, 龚光鲁, 等. 泊松点过程: 成像、跟踪和感知[M]. 北京: 科学出版社, 2013: 69–73.
      STREIT R L, SHI Xizhi, GONG Guanglu, et al. Poisson Point Process: Imaging, Tracking, and Sensing[M]. Beijing: Science Press, 2013: 69–73.

    29. [29]

      杨立, 黄河, 袁弋非, 等. 5G UDN (超密集网络)技术详解[M]. 北京: 人民邮电出版社, 2018: 233–244.
      YANG Li, HUANG He, YUAN Yifei, et al. Ultra Dense Networks of 5th Generation Mobile Communications[M]. Beijing: Posts & Telecom Press, 2018: 233–244.

    30. [30]

      蔡杰, 刘陈, 陆峰. 基于随机几何理论的多点协作网络分析[J]. 计算机技术与发展, 2016, 26(6): 200–204. doi: 10.3969/j.issn.1673-629X.2016.06.045
      CAI Jie, LIU Chen, and LU Feng. Analysis of multi-cell coordination network based on stochastic geometry approach[J]. Computer Technology and Development, 2016, 26(6): 200–204. doi: 10.3969/j.issn.1673-629X.2016.06.045

    31. [31]

      GUPTA A K, ZHANG Xinchen, and ANDREWS J G. SINR and throughput scaling in ultradense urban cellular networks[J]. IEEE Wireless Communications Letters, 2015, 4(6): 605–608. doi: 10.1109/LWC.2015.2472404

    32. [32]

      WEBB W T and STEELE R. Variable rate QAM for mobile radio[J]. IEEE Transactions on Communications, 1995, 43(7): 2223–2230. doi: 10.1109/26.392965

    1. [1]

      张海波, 李虎, 陈善学, 贺晓帆. 超密集网络中基于移动边缘计算的任务卸载和资源优化. 电子与信息学报, 2019, 41(5): 1194-1201.

    2. [2]

      李莉, 叶鹏, 彭张节, 唐延枝. 一种超密集异构网中联合干扰协调方法研究. 电子与信息学报, 2019, 41(1): 9-15.

    3. [3]

      刘江义, 王春平. 基于双马尔科夫链的势概率假设密度滤波. 电子与信息学报, 2019, 41(2): 492-497.

    4. [4]

      王凯, 李星, 兰巨龙, 卫红权, 刘树新. 一种基于资源传输路径拓扑有效性的链路预测方法. 电子与信息学报, 2019, 41(0): 1-8.

    5. [5]

      唐伦, 马润琳, 刘云龙, 王耀玮, 陈前斌. 接入与回传一体化小基站的接入控制与资源分配联合优化算法. 电子与信息学报, 2019, 41(6): 1389-1396.

    6. [6]

      全英汇, 陈侠达, 阮锋, 高霞, 李亚超, 邢孟道. 一种捷变频联合Hough变换的抗密集假目标干扰算法. 电子与信息学报, 2019, 41(0): 1-7.

    7. [7]

      赵小强, 宋昭漾. 多级跳线连接的深度残差网络超分辨率重建. 电子与信息学报, 2019, 41(10): 2501-2508.

    8. [8]

      胡炎, 单子力, 高峰. 一种面向多星多分辨率的SAR图像舰船候选区域提取方法. 电子与信息学报, 2019, 41(4): 770-778.

    9. [9]

      苏玉泽, 孟相如, 康巧燕, 韩晓阳. 核心链路感知的可生存虚拟网络链路保护方法. 电子与信息学报, 2019, 41(7): 1587-1593.

    10. [10]

      张顺外, 魏琪. 多信源多中继编码协作系统准循环LDPC码的联合设计与性能分析. 电子与信息学报, 2019, 41(10): 2325-2333.

    11. [11]

      崔苗, 喻鑫, 李学易, 张广驰, 刘怡俊. 多用户多载波无线携能通信系统的上下行联合资源分配. 电子与信息学报, 2019, 41(6): 1359-1364.

    12. [12]

      吕晓德, 张汉良, 刘忠胜, 孙正豪, 刘平羽. 基于LTE信号的外辐射源雷达同频基站干扰抑制方法研究. 电子与信息学报, 2019, 41(9): 2123-2130.

    13. [13]

      路新华, MANCHÓNCarles Navarro, 王忠勇, 张传宗. 大规模MIMO系统上行链路时间-空间结构信道估计算法. 电子与信息学报, 2019, 41(0): 1-7.

    14. [14]

      王凯, 刘树新, 陈鸿昶, 李星. 一种基于节点间资源承载度的链路预测方法. 电子与信息学报, 2019, 41(5): 1225-1234.

    15. [15]

      汤红波, 邱航, 游伟, 季新生. 基于联合备份的服务功能链可靠性保障的部署方法. 电子与信息学报, 2019, 41(0): 1-8.

    16. [16]

      曹成虎, 赵永波, 索之玲, 庞晓娇, 徐保庆. 基于频谱校正的中国余数定理多普勒频率估计算法. 电子与信息学报, 2019, 41(0): 1-8.

    17. [17]

      胡致远, 宋晓凤, 黄天聪, 李晓娣, 周瑞芳, 徐鑫, 蒙占宇, 彭强. 四表集抄通信网络虚拟化方案及组网算法研究. 电子与信息学报, 2019, 41(3): 588-593.

    18. [18]

      史久根, 徐皓, 张径, 王继. 软件定义网络中基于效率区间的负载均衡在线优化算法. 电子与信息学报, 2019, 41(3): 694-701.

    19. [19]

      赵杨, 尚朝轩, 韩壮志, 韩宁, 解辉. 分数阶傅里叶和压缩感知自适应抗频谱弥散干扰. 电子与信息学报, 2019, 41(5): 1047-1054.

    20. [20]

      黄晓舸, 樊伟伟, 曹春燕, 陈前斌. 小蜂窝网络中不活跃用户的最优能量效率资源分配方案. 电子与信息学报, 2019, 41(0): 1-8.

  • 图 1  3维多点协作蜂窝网络模型

    图 2  $n = 2$时下行链路覆盖率随基站密度变化情况

    图 3  下行链路覆盖率随SINR阈值T变化情况

    图 4  下行链路覆盖率随基站密度变化情况

    图 5  区域频谱效率随SINR阈值T的变化情况

    图 6  区域频谱效率随基站密度的变化情况

  • 加载中
图(6)
计量
  • PDF下载量:  25
  • 文章访问数:  301
  • HTML全文浏览量:  132
文章相关
  • 通讯作者:  曾孝平, zxp@cqu.edu.cn
  • 收稿日期:  2018-04-27
  • 录用日期:  2018-11-14
  • 网络出版日期:  2018-11-22
  • 刊出日期:  2019-03-01
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

/

返回文章