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正交空间调制的低复杂度检测算法 被引量:4

A low-complexity detection algorithm for quadrature spatial modulation systems
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摘要 针对正交空间调制(QSM)系统中激活天线数的不确定性、最大似然(ML)检测算法复杂度极高的缺点,提出了一种低复杂度检测算法。首先,该算法基于压缩感知(CS)信号重构理论,对系统模型进行重构,使固定激活天线系统中的低复杂度算法可以在新的系统模型中使用;然后,借鉴正交匹配追踪(OMP)算法的思想,选出一个激活天线备选集;最后,通过ML算法搜索备选集,选出激活天线和调制符号。仿真结果显示,相比ML检测算法,所提算法在性能丢失较小的情况下,降低了约90%的复杂度。 To tackle the issues of the uncertainty number of the activated antennas and high computational complexity of maximum likelihood (ML) detection algorithm in quadrature spatial modulation (QSM), a low-comp!exity detec- tion algorithm was proposed. Firstly, the system model was reconstructed into a new model suitable for low-complexity detection algorithms in fixed active antennas systems based on compressed sensing (CS) signal re- construction theory. Then, based on the idea Of orthognnal matching pursuit (OMP) algorithm and reconstructed model, a candidate set of activated antennas was obtained. Lastly, using ML algorithm to search the candidate, the index of activated antennas and the modulation symbol were selected. Simulation results show that the proposed de- tector is capable of achieving about 90% reduction in complexity with low performance loss compared with ML al- gorithm.
出处 《电信科学》 北大核心 2017年第5期75-81,共7页 Telecommunications Science
基金 国家科技重大专项基金资助项目(No.2016ZX03002010-003)~~
关键词 正交空间调制 空间调制 广义空间调制 压缩感知 最大似然 正交匹配追踪 quadrature spatial modulation, spatial modulation, generalized spatial modulation, compressed sensing,maximum likelihood, orthogonal matching pursuit
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  • 13 rd Generation Partnership Project.TR 25.913-900.Requirements for Evolved UTRA(E-UTRA)and Evolved UTRAN(E-UTRAN),2009.
  • 23rd Generation Partnership Project.TR 36.912-900.Feasibility Study for Further a Advancements for E-UTRA(LTE-Advanced),2011.
  • 3Marzetta L T.Noncooperative cellular wireless with unlimited numbers of base station antennas.IEEE Transactions on Wireless Communications,2010,9(11):3590-3600.
  • 4Rusek F,Persson D,Lau B K,et al.Scaling up MIMO:opportunities and challenges with very large arrays.Signal Processing Magazine,2013,30(1):40-60.
  • 5Lu L,Li G Y,Swindlehurst L A,et al.An overview of massive MIMO:benefits and challenges.IEEE Journal of Selected Topics in Signal Processing,2014,8(5):742-758.
  • 6Larsson G E,Edfors O,Tufvesson F,et al.Massive MIMO for next generation wireless systems.IEEE Communications Magazine,2014,52(2):186-195.
  • 7Adhikary A,Nam J,Ahn J,et al.Joint spatial division and multiplexing-the large-scale array regime.IEEE Transactions on Information Theory,2013,59(10):6441-6463.
  • 8Sun C,Gao X Q,Jin S,et al.Beam division multiple access transmission for massive MIMO.IEEE Transactions on Communications,revised.
  • 9Nam J,Ahn J,Adhikary A,et al.Joint spatial division and multiplexing:realizing massive MIMO gains with limited channel state information.Proceedings of Information Sciences and Systems(CISS),Princeton,New Jersey,USA,2012:1-6.
  • 10Nam J,Adhikary A,Ahn J,et al.Joint spatial division and multiplexing:opportunistic beamforming,user grouping and simplified downlink scheduling.IEEE Journal of Selected Topics in Signal Processing,2014,8(5):876-890.

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