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LR算法在MIMO-LAS-CDMA系统中的应用 被引量:3

Application of Lattice Reduction Algorithm in MIMO-LAS-CDMA Systems
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摘要 在多入多出系统中,使用减格算法进行信号检测,如果结合多用户检测算法可以达到接近极大似然检测的性能。为了达到这个目的,给定多入多出系统的信道矩阵需要转化成一个正交的矩阵,以减小或消除信号检测过程中常规迫零算法对噪声的放大作用。为此,将减格算法与常规迫零检测算法结合,分析和仿真了接收机中使用减格辅助的迫零算法在M IMO-LAS-CDMA系统中的性能。仿真结果显示,使用这个新算法在复杂度开销增加不大的情况下,性能上超过了使用迫零算法接收机的系统。 LR(Lattice-Reduction) -aided algorithm for signal detection in MIMO ( Multi-Input Multi-Output) systems has been proposed recently. The near maximum-likelihood detection performance can be achieved by employing the LR-aided multiuser detection algorithms. The channel matrix of the MIMO systems needs to be changed into an orthogonal matrix, so the noise enhancement by using ZF (Zero-Forcing) algorithm can be reduced. In this paper, we adopted the LR-aided ZF algorithm to MIMO-LAS-CDMA systems. The BER performance of the system employing LR-ZF receiver is simulated and analyzed. The simulation results show that the BER (Bit-Error-Rate) performance of the system employing LR-ZF receiver outperformed that of ZF receiver distinctly at the expense of little increase of computation complexity.
出处 《吉林大学学报(信息科学版)》 CAS 2006年第1期12-17,共6页 Journal of Jilin University(Information Science Edition)
基金 国家自然科学基金资助项目(69931050)
关键词 大区域同步 码分多址 多人多出 迫零 减格 large area synchronous code division multiple access multi-input multi-output zero-forcing lattice-reduction
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参考文献8

  • 1LI Dao-ben. The Perspectives of LAS-CDMA (Large Area Synchronous CDMA) Technology for the 4th Generation of Wireless Mobile Radio [J]. IEEE Communications Magazine, 2003, 23 (2) : 128-134.
  • 2YAO H, WORNELL G. Lattice-Reduction-Aided Detectors for MIMO Communication Systems [ CL/OL]. IEEE Proc Global Communications Conference (GLOBECOM), Taipei, Taiwan, 2002 [2004-12-25]. http: //allegro. mit. edu//bin/pubs - search, php? SearchFor = conference.
  • 3DIRK WUBBEN, RONALD BOHNKE. MMSE-Based Lattice-Reduction for Near-ML Detection of MIMO Systems[CL/OL].ITG Workshop on Smart Antennas, Munich, Germany, 2004 [2004-12-25]. http: //www. comm. uni - bremen, de/whomes/wuebben/.
  • 4YAO H. Efficient Signal, Code, and Receiver Designs for MIMO Communication Systems[D]. [ S. l. ] : Massachusetts Institute of Technology, 2003.
  • 5WINDPASSINGER C, FISCHER R F H. Low-Complexity Near-Maximum-Likelihood Detection and Precoding for MIMO Systems using Lattice Reduction [C] //Proc IEEE Information Theory Workshop (ITW), Paris, France: [s. n. ], 2003.
  • 6WINDPASSINGER C, H FISCHER R F. Optimum and Sub-Optimum Lattice-Reduction-Aided Detection and Precoding for MIMO Communications[C] //Proc Canadian Workshop on Information Theory, Waterloo, Ontario, Canada: [ s. n. ],2003 : 88-91.
  • 7LENSTRA A K, LENSTR H W, LOVASZ L. Factoring Polynomials with Rational Coefficients[J]. Math Ann, 1982(261) : 515-534.
  • 8GOLDEN G D, FOSCHINI G J. Detection Algorithm and Initial laboratory Results Using V-blast Space-Time Communication Architecture[J]. Electron Lett, 1999, 35 (1) : 1416-1418.

同被引文献27

  • 1JANKIRAMAN M. Space - time codes and mimo systems [ M ]. Artech House, 2004.
  • 2WINDPASSINGER C, FISCHER R F H, HUBER J B. Lattice - reduction - aided broadcast precoding [ J ]. IEEE Trans, Comm, 2004,52:2057-2060.
  • 3LENSTRA, LENSTR, LOVASZ. Factoring Polynomials with Rational Coefficients[J]. Math. , Ann, 1982, 261 : 515 -534.
  • 4NIU Jun, LU I Tai. A comparison of two lattice - reduction - based receivers for mimo systems[ C ]. Sarnoff Symposium 2008 IEEE,2008.
  • 5GAN Yinghung, LING Cong. Member, IEEE, and MOW Wai - Ho, Senior Member[ C ]//IEEE. Complex Lattice Reduction Algorithm for Low - Complexity Full Diversity MIMO Detection. IEEE Transactions on signal processing,2009,57 ( 7 ) :2701 - 2710.
  • 6WINDPASSINGER C. Detection and precoding for multiple input multiple output channels [ D ]. Erlangen - Nuernberg : Friedrich - Alexander - University ,2004.
  • 7HASSIBI B,VIKALO H. On the Sphere - Decoding Algorithm I [ J ]. IEEE Transactions on signal processing, 2005,53(8) :2819 -2834.
  • 8DAMEN M O, EIGAMALH, CAIRE G. On Maximum - Likelihood Detection and the Search for the closest Lattice Point [ J ]. IEEE Transactions on information theory, 2003, 49(10) :2389 -2402.
  • 9GOLUB G H, CIOFFI J M. Matrix Computations [ C ]. 3rd edition. The Johns Hopkins University Press, Baltimore, MD, USA, 1996.
  • 10BARBERO L G, RATNARAJAH T,COWAN C. A comparison of complex lattice reduction algorithms for MIMO detection [ J ]. IEEE International conferences on Acoustics, Speech and Signal Processing, 2008 (4):2705 - 2708.

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