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基于Sorenson相似系数的快速天线选择算法 被引量:1

Fast Antenna Selection Algorithm Based on Sorenson Similarity Coefficient
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摘要 穷举搜索天线选择算法的计算复杂度随天线的增多变大,影响实际应用。针对该问题,提出基于Sorenson相似系数的快速天线选择算法。利用Sorenson相似系数来表征信道矩阵行向量间的相关性,通过逐行递增的方法,选择相似系数最小且行范数最大的接收天线,从而最大程度地增加系统容量。仿真结果表明,该算法在射频链路较少时计算复杂度很低,且能获得接近最优算法的中断容量。 The antenna selection algorithm is the exhaustive search method.Its computational complexity grows rapidly as the number of antennas increases.It is quite impractical.Focusing on this problem,a fast antenna selection algorithm based on Sorenson similarity coefficient is proposed.It uses Sorenson similarity coefficient to express the correlation of two vectors,and selects the receive antennas with the largest norm and smallest similarity coefficient by searching the matrix row by row,so the system capacity can be increased most.Simulation results indicate that the capacity of the proposed algorithm is close to that of the optimal exhaustive search algorithm and its computational complexity is low in the case where the number of radio frequency chains is small.
作者 华玲 秦立新
出处 《计算机工程》 CAS CSCD 北大核心 2011年第16期108-110,共3页 Computer Engineering
关键词 多输入多输出 天线选择 信道容量 Sorenson相似系数 Multiple Input Multiple Output(MIMO) antenna selection channel capacity Sorenson similarity coefficient
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参考文献6

  • 1马小晶,刘亮,叶凡,任俊彦.基于可配置型K-Best的MIMO信号检测器[J].计算机工程,2009,35(24):236-238. 被引量:7
  • 2汪洋,宋娇,葛临东.一种基于范数和相关的MIMO接收天线选择新算法[J].计算机工程与应用,2007,43(32):132-134. 被引量:2
  • 3Molisch A F,Win M Z,Choi Y S,et al.Capacity of MIMO Systems with Antenna Selection. IEEE Trans.on Wireless Communication . 2005
  • 4Y.S. Choi,A.F.Molisch,M.Z. Win,and J.H. Winters."Fast antenna selection algorithms for MIMO systems. Proc. VTC . 2003
  • 5Telatar IE.Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications . 1999
  • 6Joo-Seok Park,Dong-Jo Park.A new antenna selection algorithm with low complexity for MIMO wireless systems. 2005 IEEE International Conference on Communications, ICC’05 . 2005

二级参考文献11

  • 1Wenk M, Zellweger M. K-Best MIMO Detecting VLSI Architectures Achieving up to 424Mbps[C]//Proc. of the IEEE Int'l Syrup. on Circuits and Systems.[S. l.]: IEEE Press, 2006.
  • 2Zhao Wanlun, Giarmakis G B. Reduced Complexity Closest Point Decoding Algorithms for Random Lattices[J]. IEEE Transactions on Wireless Communications, 2006, 5(1): 101-111.
  • 3Burg A, Borgmann M, Wenk M, et al. VLSI Implementation of M1MO Detection Using the Sphere Decoding Algorithm[J]. IEEE Journal of Solid-State Circuits, 2005, 40(7): 1566-1577.
  • 4Barbero L G. Rapid Prototyping of a Fixed-throughput Sphere Decoder for MIMO Systems[C]//Proc. of the IEEE International Conference on Communications. [S. l.]: IEEE Press, 2006.
  • 5Paulraj A J,Nabar R U,Gore D A.Introduction to space-time wireless communications[M].England:Cambridge University Press,2003.
  • 6Foschini G J.On limits of wireless communication in a fading environment when using multi-element antennas[J].Wireless Communication,1998,6(30):311-335.
  • 7Molisch A F,Win M Z.MIMO Systems with antenna selection[J].IEEE Microwave Magazine,2004,5(1):46-56.
  • 8Sanayei S,Nosratinia A.Antenna selection in MIMO systems[J].IEEE Communications Magazine,2004,42 (10):68-73.
  • 9Gorokhov A,Gore D A,Paulraj A J.Receive antenna selection for MIMO spatial multiplexing:theory and algorithms[J].IEEE Transactions on Signal Processing,2003,51 (11):2796-2807.
  • 10Gore D A,Gorokhov A,Paulraj A J.Joint MMSE verus V-BLAST and antenna selection[J].Signal Systems and Computers,2002,1 (11):505 -509.

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