期刊文献+

MIMO-OFDM系统中基于QR分解的检测算法研究

Detecting Algorithms of MIMO-OFDM Systems Based on QR Decomposition
下载PDF
导出
摘要 重点介绍了MIMO-OFDM系统中基于QR分解的几种信号检测算法,分析了各种算法的优缺点;指出信号检测顺序是降低误差传播的关键。基于改进的Gram-Schmidt正交排序QR检测算法用迭代运算代替矩阵求逆运算,有效地改进了传统算法的缺点,降低了计算量,使系统在复杂度和性能之间取得了良好的折中,并在最后对该算法与MMSE准则联合的算法进行了介绍。 In this paper, several signal detection algorithms based on QR decomposition as applied to MIMO-OFDM systems are studied and their characteristics are analyzed. It is a key to reduce the error probability by sorting the detection sequence. The sorted QR decomposition of the channel matrix is base on the improved Gram-schmidt, which uses iterative operation instead of contrary matrix operation, so the shortcomings of traditional detection algorithms are improved and the computational complexity is effectively reduced. This algorithm can gain the good tradeoffs between the performance and the complexity. SQRD algorithm combined with the MMSE cri- teflon algorithm is described finally.
作者 覃博 林云
出处 《山西电子技术》 2012年第5期53-54,69,共3页 Shanxi Electronic Technology
关键词 MIMO—OFDM QR分解 Gram-Schmidt排序算法 SQRD算法 MIMO-OFDM QR decomposition Gram-Schmidt algorithm SQRD
  • 相关文献

参考文献6

  • 1Jee - Hye Lee,Myung - Sun Back, Hyoung - KyuSong.Efficient MIMO Receiving Technique in IEEE 802. 11 nSystem for Enhanced Services [ J ]. IEEE Trans. ConsumElectron,2007,35:344 -349.
  • 2周健,张冬.MIMO-OFDM系统中的信号检测算法(Ⅰ)[J].南京工程学院学报(自然科学版),2010,8(1):15-23. 被引量:2
  • 3Tarokh V,Naguib A,Seshadri. Combined Array Processingand Space - time Coding[ J ]. IEEE Trams. Inform. Theo-ry ,1999,45 : 1121 -1128.
  • 4Wubben D,kuhn k,kammeyer KD. MMSE Extension of V-BLAST Based on Sord QR Decomposition[ M]. IEEESemiannual Vehicular Technoligy Conference ( VTC2003- Fall) , Orlando, Florida, US A, October,2003.
  • 5MURUGAN AD,EL GAMAL H,DAMEN MO. A UnifiedFramework for Tree Search Decoding : Rediscovering theSequential Decoder. [ EB/OL]. [ 2010 -07 -06].
  • 6Ronald B, Dirk W, Volker K,et al. Reduced ComplexityMMSE Detection for BLAST A rchitectures [ J ]. IEEEGlobal Telecommunications Conference,2003 ( 4 ) : 2258-2262.

二级参考文献13

  • 1HELMUT B O. Principles of MIMO- OFDM Wireless Systems[ M]. Boca Raton: CRC Press, 2005.
  • 2GOLDEN G D, FOSCHIN1 G J, VALENZUELA R A. Detection algorithm and initial laboratory results using the V-BLAST space-time commu- nication architecture[ J]. IEEE Electron Letter, 1999, 35 ( 1 ) : 14 - 15.
  • 3VERD U. Muhiuser Detection[ M]. New York: Cambridge Univ. Press, 1998.
  • 4SELLATHURAI M, HAYKIN S. A simplified diagonal BLAST architecture with iterative parallel interference cancellation receivers [ C ]// IEEE International Conference on Communications, 2001 : 3067 -3071.
  • 5FOSCHINI G J, GOLDEN G D, VALENZUELA R A. Simplified processing for high spectral efficiency wireless communication employing muhi-element arrays[ J]. JSAC 1999, 17 ( 11 ) : 1841 - 1852.
  • 6HAROLD A, DOMINIK S, FRANZ H. Efficient Detection Algorithms for MIMO Channels: A Geometrical Approach to Approximate ML Detection [ J ]. IEEE Transactions on Signal Processing, 2003, 51 ( 11 ) : 2808 - 2820.
  • 7MOHAMED O D, GAMAL H E, GIUSEPPE C. On maximum-likelihood detection and the search for the closest lattice point [ J ]. IEEE Transactions on Information Theory, 2003, 49(10) : 2389 -2402.
  • 8GAMAL H E, CAIRE G, DAMEN M O. Lattice coding and decoding achieves the optimal diversity-multiplexing tradeoff of MIMO channels [ J ]. IEEE Transactions on Information Theory, 2004, 50 (6) : 968 -985.
  • 9VIKALO H, HASSIBI B, MITRA U. Sphere-constrained ML detection for frequency-selective channels[ J]. IEEE Transactions on Communications, 2006, 54(7): 1179-1183.
  • 10DAMEN M O, H El Gamal, CAIRE G. On Maximum-Likelihood Detection and the Search for the Closest Lattice Point. 1EEE Transactions on Information Theory, 2003, 49 (10) : 2389 - 2402.

共引文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部