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多用户大规模MIMO自适应安全传输策略

金梁 宋昊天 钟州 许晓明

金梁, 宋昊天, 钟州, 许晓明. 多用户大规模MIMO自适应安全传输策略[J]. 电子与信息学报, 2018, 40(6): 1468-1475. doi: 10.11999/JEIT170974
引用本文: 金梁, 宋昊天, 钟州, 许晓明. 多用户大规模MIMO自适应安全传输策略[J]. 电子与信息学报, 2018, 40(6): 1468-1475. doi: 10.11999/JEIT170974
JIN Liang, SONG Haotian, ZHONG Zhou, XU Xiaoming. Adaptive Secure Transmission Strategy for Multiuser Massive MIMO[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1468-1475. doi: 10.11999/JEIT170974
Citation: JIN Liang, SONG Haotian, ZHONG Zhou, XU Xiaoming. Adaptive Secure Transmission Strategy for Multiuser Massive MIMO[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1468-1475. doi: 10.11999/JEIT170974

多用户大规模MIMO自适应安全传输策略

doi: 10.11999/JEIT170974
基金项目: 

国家 863 计划项目(2015AA01A708),国家自然科学基金(61471396, 61701538, 61601514, 61501516, 61521003)

Adaptive Secure Transmission Strategy for Multiuser Massive MIMO

Funds: 

The National 863 Program of China (2015AA01A708), The National Natural Science Foundation of China (61471396, 61701538, 61601514, 61501516, 61521003)

  • 摘要: 大规模MIMO系统采用空分多址可以提高系统吞吐量,同时利用多用户下行信号的相互协作可以对窃听者造成叠加干扰,带来了天然的安全增益。但目前该系统的物理层安全研究仍采用传统的人工噪声方案,忽略了多用户信号干扰带来的安全增益,造成严重的功率浪费。针对这一问题,该文分析了多用户信号干扰对系统可达平均安全速率和平均安全能效的影响,给出了系统的最佳接入用户区间。研究发现,在系统接入用户数较少和用户数较多时,系统安全能力较弱,针对此分别提出了N波束加扰和基于用户位置的用户调度的自适应安全传输策略。最后通过仿真验证了理论推导和所提策略的有效性,利用该文所提策略,能够保证系统天然安全能力不足时的安全通信。
  • ZHU Jun, SCHOBER R, and BHARGAVA V K. Secure transmission in multicell massive MIMO systems[J]. IEEE Transactions on Wireless Communications, 2014, 13(9): 4766-4781. doi: 10.1109/TWC.2014.2337308.
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    ZHU Jun, SCHOBER R, and BHARGAVA V K. Linear precoding of data and artificial noise in secure massive MIMO systems[J]. IEEE Transactions on Wireless Communications, 2016, 15(3): 2245-2261. doi: 10.1109/TWC.2015.2500578.
    ZHU Jun and WEI Xu. Securing massive MIMO via power scaling[J]. IEEE Communications Letters, 2016, 20(5): 1014-1017. doi: 10.1109/LCOMM.2016.2532328.
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    DENG Yansha, WANG Lifeng, WONG K K, et al. Safeguarding massive MIMO aided hetnets using physical layer security[C]. Wireless Communications Signal Processing, Nanijing, China, 2015: 1-5. doi: 10.1109/WCSP. 2015.7341120.
    ZHAO Long, ZHENG Kan, LONG Hang, et al. Performance analysis for downlink massive MIMO system with ZF precoding[J]. Transactions on Emerging Telecommunications Technologies, 2014, 25(12): 1219-1230. doi: 10.1002/ett.2745.
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    BJORNSON E, SANGUINETTI L, HOYDIS J, et al. Designing multi-user MIMO for energy efficiency: When is massive MIMO the answer?[C]. Wireless Communications and Networking Conference, Istanbul, Turkey, 2014: 242-247. doi: 10.1109/WCNC.2014.6951974.
    MARZETTA T L. Noncooperative cellular wireless with unlimited numbers of base station antennas[J]. IEEE Transactions on Wireless Communications, 2010, 9(11): 3590-3600. doi: 10.1109/TWC.2010.092810.091092.
    LIU Haijing, GAO Hui, YANG Shaoshi, et al. Low- complexity downlink user selection for massive MIMO systems[J]. IEEE Systems Journal, 2017, 11(2): 1072-1083. doi: 10.1109/JSYST.2015.2422475.
    HE Anqi, WANG Lifeng, ELKASHLAN M, et al. Spectrum and energy efficiency in massive MIMO enabled hetnets: A stochastic geometry approach[J]. IEEE Communications Letters, 2015, 19(12): 2294-2297. doi: 10.1109/LCOMM.2015. 2493060.
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出版历程
  • 收稿日期:  2017-10-17
  • 修回日期:  2018-01-16
  • 刊出日期:  2018-06-19

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