期刊文献+

一种用于MIMO检测中的QR快速分解算法 被引量:6

A fast QR decomposition algorithm for MIMO detection
下载PDF
导出
摘要 针对多输入多输出系统中常用的非线性检测算法,如排序QR分解(Sorted QR Decomposition,SQRD)、球型译码(Sphere Decoding,SD)、K-Best或QRM(QR Decomposition and M algorithm)等,提出了一种具有最优检测顺序的QR快速分解方法,作为检测前的预处理操作。该算法首先对信道矩阵进行第一次QR分解,根据所得上三角矩阵R可确定最优的检测顺序,并按该顺序对R进行列重排。然后对R进行第二次QR分解,即得具有最优检测顺序的QR分解结果。与现有的基于R对角元素的模值排序的QR分解算法相比,本算法可保证检测顺序最优从而性能最优。仿真结果表明天线配置为4×4和6×6时,在误码率10^(-3)处可节约信噪比分别为:1dB和2dB;与现有的基于信干噪比排序的QR分解算法相比,本算法与其性能一致的基础上可节约25%的复乘法次数和33%的复加法次数。 A fast QR decomposition algorithm with optimal detection order is proposed in this paper for common used MIMO non- linear detection, including sorted QR decomposition (SQRD) , sphere decoding (SD), K-best/QR decomposition and M algorithm (QRM) and so on. Using this algorithm, the receiver does QR decomposition of the channel matrix firstly, determines the best order of detection from the upper triangular matrix: R, and arranges the columns of R according to the optimal detection order; then, the receiver does QR decomposition of the rearrangement matrix of R for a second time, which is the QR decomposition results with the optimal detection order. Compared with the existing QR decomposition algorithm, getting its detection order according to the diagonal elements' modulus of R, the proposed fast QR decomposition algorithm can improve detection performance because of its optimal detection order. Simulation results show when bit error rate (BER) equals 10-3 with the antenna configuration being 4x4 and 6x6, the proposed algorithm can save signal to noise ratio (SNR) in 1 dB and 2 dB, respectively. Compared with the existing QR decomposition algorithm, getting its detection order according to signal to interference and noise ratio (SINR) , the proposed algorithm can reduce 25% times of complex multiplications and 33% times of complex additions with the same BER performance.
出处 《信号处理》 CSCD 北大核心 2011年第8期1147-1152,共6页 Journal of Signal Processing
基金 国家重大科技专项资助项目(2009ZX03005-003-02):面向重点行业应用的宽带无线多媒体接入系统开发与示范应用 国家自然科学基金项目(60976022):面向可重构Gbps VLSI的MIMO检测关键技术研究 中央高校基本科研业务费专项资金资助(2009RC01 15)
关键词 非线性检测 QR 最优检测顺序 non-linear detection QR optimal detection order
  • 相关文献

参考文献10

  • 1Paulraj A., Nabar R., and Dhananjay G.. Introduction to space-time wireless communications [ M ]. Cambridge Uni- versity Press, 2003. 1-270. 被引量:1
  • 2林文峰..MIMO无线通信系统的迭代检测技术研究[D].上海交通大学,2009:
  • 3史开新..MIMO系统中信号检测技术的研究[D].西安电子科技大学,2008:
  • 4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
  • 5Radji D., Leib H.. Interference cancellation based detec- tion for V-BLAST with diversity maximizing channel parti- tion[J]. IEEE Journal of Selected Topics in Signal Pro- cessing, 2009, 3(6) : 1000-1015. 被引量:1
  • 6Chen J. M., Jin S., and Wang Y. G.. Reduced complexity MMSE-SIC detector in V-BLAST systems [ C ] //PIMRC 2007. Athens, 2007. 1-5. 被引量:1
  • 7Xiang X. W., Zhong W.. Novel K-best detection algorithms for MIMO system [ J]. Journal of Southeast University ( English Edition), 2009, 25 ( 1 ) : 1-5. 被引量:1
  • 8Fukatani T., Matsumoto R. and Uyematsu T.. Two meth- ods for decreasing the computational complexity of the MI- MO ML decoder[ C]//IEICE Trans Fund Electron Com- mun Comput Sci. Oxford University Press, 2004. 2571- 2576. 被引量:1
  • 9Seethaler D, Blolcskei H. Performance and complexity a- nalysis of infinity-norm sphere-decoding[ J ]. IEEE Trans- action on Information Theroy, 2010, 56 ( 3 ) : 1085-1105. 被引量:1
  • 10Wang Z. P. , Zhang S. Z.. Improved SQRD algorithm for MIMO-BLAST systems [ C ] //ICCT. Hangzhou, 2008. 183-185. 被引量:1

二级参考文献8

  • 1Foschini G J,Gans M J.On limits of wireless communications in a fading environment when using multiple antennas[J].Wireless Personal Communications,1998,6(3):311-335. 被引量:1
  • 2Foschini G J.Layered space-time architecture for wireless communication in a fading environment when using mul-tielement antennas[J].Bell Labs Technical Journal,1996,1(2):41-49. 被引量:1
  • 3Foschini G J,Wolniansky P W,Golden G D.V-BLAST:an architecture for realizing very high data rates over the rich-scattering wireless channel[C]∥1998 International Symposium on Signals,Systems and Electronics (ISSSE1998).Pisa:IEEE Press,1998:295-300. 被引量:1
  • 4Golden G D,Foschini G J.Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture[J].Electronics Letters,1999,35(1):14-16. 被引量:1
  • 5Wubben D,Bohnke R,Kuhn V,et al.MMSE extension of V-BLAST based on sorted QR decomposition[C]∥VTC 2003-Fall.[S.l.]:IEEE Press,2003:508-512. 被引量:1
  • 6Gantmakher F R.The theory of matrices[M].New York:Chelsea Publishing Company,1989:25-62. 被引量:1
  • 7Wai W K, Tsui Chi-Ying, Cheng R S. A low complexity architecture of the V-BLAST system[C]//WCNC2000 IEEE. Chicago: [s.n.], 2000: 310-314. 被引量:1
  • 8陶小峰,俞追专,秦海燕,张平.V-BLAST的次优译码[J].电子学报,2003,31(5):703-706. 被引量:8

共引文献8

同被引文献42

  • 1周亮,邱玲,朱近康.MIMO通信系统中一种新的自适应均衡方法[J].电子与信息学报,2006,28(10):1862-1865. 被引量:6
  • 2赵辰,刘应状,朱光喜.VLST系统中ZF检测算法的研究[J].无线电通信技术,2007,33(2):37-39. 被引量:5
  • 3J. Mietzner, R. Schober, L. Lampe, W. H. Gerstackerand P. A. Hoeher. Multiple-antenna techniques for wirelesscommunications . acomprehensive literature survey [ J ].IEEE Commu. Surveys & Tutorials, 2009,11(2) ; 87-105. 被引量:1
  • 4F. Rusek, D. Persson, B. Lau, E. Larsson, T. Marzetta, 0.Edfors and F. Tufvesson. Scaling up MIMO : Opportuni-ties and challenges with very large arrays[ J] . IEEE Sig-nal Processing Magazine, 2012,30( 1) ; 40-60. 被引量:1
  • 5E.G. Larsson. MIMO detection methods : How they work [J].IEEE, Signal Process. Mag. , 2009 , 26(3) : 91-95. 被引量:1
  • 6K. S. Schneider. Optimum detection of code division multi-plexed signals [ J ]. IEEE Trans. Aerosp. Elect. Syst.,1979,15(1): 181-185. 被引量:1
  • 7M. Honig, U. Madhow and S. Verdu. Blind adaptivemultiuser detection[J]. IEEE Trans. Inf. Theory, 1995,41(4): 994-960. 被引量:1
  • 8G. D. Golden, G. J. Foschini,R. A. Valenzuela and P.W. Wolniansky. Detection algorithm and initial laboratoryresults using V-BLAST space-time communication archi-tecture [ J ]. Electron. Lett.,1999, 35 (1) : 14-16. 被引量:1
  • 9B, SundarRajan, S. K. Mohammed, A. Chockalingamand N. Srinidhi. Low-complexity near-ML decoding oflarge non-orthogonal STBC susing reactive tabu search[C]// In Proc. IEEE Int. Symp. Info. Theory, Seoul,Korea, 2009: 1993-1997. 被引量:1
  • 10A. D. Murugan, H. El Gamal, M. 0. Damen and G.Caire. A unified framework for tree search decoding : re-discovering the sequential decoder [ J ]. IEEE Trans.Inf. Theory, 2006, 52(3) : 933-953. 被引量:1

引证文献6

二级引证文献11

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