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MIMO-OFDM系统中一种改进的V-BLAST检测算法 被引量:8

An Improved Algorithm for V-BLAST Detection in MIMO-OFDM System
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摘要 在V-BLASTMIMO-OFDM系统中,ML算法是检测信号的最佳方式,但是算法的复杂度随着天线数目呈指数增长,因此很难在实际中得到应用。OSIC算法可以降低算法的复杂度,但是其误码率性能也下降了,降低的原因是无法防止误码的扩散。本文提出的ML-OSIC算法,是ML与OSIC的结合,在减少ML算法搜索次数的同时,能有效地避免层间干扰和误码扩散。仿真结果表明,本算法在降低算法复杂度的同时,得到了与ML算法很接近的性能。 In V-BLAST MIMO-OFDM system, ML detection algorithm is the best way, but the complexity of the algorithm is exponential growth with the number of transmission antennas. So it is difficult for the ML detection algorithm to be applied in practice. OSIC algorithm reduces the complexity of the detection with poorer performance compared with ML,because it is unable to prevent the diffusion of bit error. In this paper,ML-OSIC algorithm is proposed by combining ML and OSIC. This algorithm can reduce the search times of ML, while the sub-layers interference and the diffusion of bit error can be avoided. The simulation results show that the algorithm reduces the complexity of algorithm and gets almost the same performance as ML algorithm.
作者 汪蓓 朱琦
出处 《信号处理》 CSCD 北大核心 2009年第9期1409-1413,共5页 Journal of Signal Processing
基金 国家重点基础研究发展计划资助(2007CB310607) 国家自然科学基金(60772062 60872018) 东南大学移动通信国家重点实验室开放研究基金资助课题(N200813) 江苏省科技计划项目(BG2006039)
关键词 检测算法 V-BLAST MIMO-OFDM 最大似然算法 detection algorithm V-BLAST MIMO-OFDM Maximum Likelihood Algorithm(ML)
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参考文献10

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同被引文献60

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  • 2唐普英,李志辉,黄顺吉.基于遗传算法和禁忌搜索的多用户检测器[J].电子科技大学学报,2004,33(5):499-502. 被引量:2
  • 3张金荣,王东,曹长修,唐贤伦.一种空间相关的Nakagami-m衰落下MIMO-OFDM系统误码率计算方法[J].郑州大学学报(工学版),2007,28(2):73-76. 被引量:3
  • 4罗振东,赵明,刘思杨,刘元安.一种新型的快速递归V-BLAST检测算法[J].电子与信息学报,2007,29(7):1546-1550. 被引量:3
  • 5郭志恒,李立华,陶小峰.快速V-BLAST排序检测方法[J].北京邮电大学学报,2007,30(4):83-87. 被引量:9
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  • 9A.Benjebbour,H.Murata,and S.Yoshida.Comparison of ordered successive receivers for space-time transmission[C].in Proc.VTC 2001 Fall,Atlantic City,New Jersey,US:Oct.7-11,2001.vol.4,pp.2053-2057.
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