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基于低复杂度算法的QPSK多用户检测 被引量：2

Multiuser Detection Based on a Low-coplexity Algorithm
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摘要 提出了一种低复杂度的QPSK准最优多用户检测算法。该算法保证在多项式复杂度下收敛到全局最优解附近。实验和仿真结果表明:该算法性能十分逼近最优多用户检测器,为解决CDMA系统的多用户检测问题提供了一条新的途径。 In this paper, it proposes a low-complexity quasi-optimum multiuser detection algorithm. This approach guarantees to converge the global optimum under the computational complexity of polynomial, which can efficiently solve the nondeterministic-time hard problem in the maximum likelihood multiuser detection. Simulations show that the proposed method has lower complexity and can offer good performance.
作者 邹曙光
机构地区 南京工程学院通信工程系
出处 《山西电子技术》 2009年第1期14-15,17,共3页 Shanxi Electronic Technology
关键词 多用户检测 QPSK 近似算法 multiuser detect QPSK approximation algorithm
分类号 TN911.23 [电子电信—通信与信息系统]
  • 相关文献

参考文献8

  • 1Verdu S.Minimum Probability or Error for Asynchronous Gaussian Multiple-Access Channels[J].IEEE Trans Inform Theory,1986,32(1):85-96.
  • 2Ma W K,Davidson T N,Wong K M,et al.Efficient Quasi-Maximum-Likelihood Multiuser Detection by Semidefinite Relaxation[J].IEEE International Conference on Communications,2001:6-10.
  • 3Tan P H,Rasmussen L K.The Application of Semidefinite Programming for Detection in CDMA[J].IEEE J Select Areas Commun,2001,19(8):1442-1449.
  • 4Schlegel C,Wei L.A Simple Way to Compute the Minimum Distance in Multiuser CDMA system[J].IEEE Trans Commun,1997,45(5):532-535.
  • 5Kechriotis G I,Manolakos E S.Hopfield Neural Network Implementation of the Optimal CDMA Multiuser Detector[J].IEEE Trans Neural Netw,1996,7(1):131-141.
  • 6Nelson L B,Poor H V.Iterative Multiuser Receivers for CDMA Channels:An EM-Based Approach[J].IEEE Trans Commun,1996(44):1770-1710.
  • 7Ma W K,Davidson T N,Wong K M,et al.Efficient Quasi-Maximum-Likelihood Multiuser Detection by Semi-definite Relaxation[J].IEEE International Conference on Communications,2001:6-10.
  • 8Ye Y.Approximating Quadratic Programming with Bou-nd and Quadratic Constraints[J].Math Program,1999,84:219-226.

同被引文献13

  • 1Verdu S. Minimum Probability or Error for Asynchronous Gaussian Multiple-access Channels [ J ]. IEEE Trans Inform Theory, 1986,32 ( 1 ) : 85 - 96.
  • 2Ma W K,-Davidson T N, Wong K M, et al. Efficient Quasi-Maximum-Likelihood Multiuser Detection by Semidefinite Relaxation[ J]. IEEE International Conference on Communications ,2001:6 -10.
  • 3Tan P H, Rasmussen L K. Tile Application of Semidefinite Programming for Detection in CDMA[ J]. IEEE J Select Areas Commun,2001,19 (8) : 1442 - 1449.
  • 4Huaiyu Dai, Poor HV. Iterative Space-time Processing for Muhiuser Detection in Multipath CDMA Channels [ J ]. IEEE Trans Signal Processing Sept,2002,50 ( 9 ) : 2116 - 2127.
  • 5Schlegel C, Wei L. A simple Way to Compute the Minimum Distance in Multiuser CDMA System [ J ]. IEEE Trans Commun, 1997,45 (5) :532 - 535.
  • 6Kechfiotis G I, Manolakos E S. Hopfield Neural Network Implementation of the Optimal CDMA Multiuser Detector [ J ]. IEEE Trans Neural Netw, 1996,7 ( 1 ) : 131 - 141.
  • 7Nelson L B, Poor H V. Iterative Multiuser Receivers for CDMA Channels: An EM-based Approach [ J ]. IEEE Trans Commun, 1996,44 : 1770 - 1710.
  • 8Wang X, Poor H V. Blind Equalization and Multiuser Detection in Dispersive CDMA Channels [ J]. IEEE Trans Commun, 1998,46( 1 ) :91 - 103.
  • 9Ye Y. Approximating Quadratic Programming with Bound and Quadratic Constraints [ J ]. Math Program, 1999,84 : 219 -226.
  • 10Qingyu Li, Er-Wei Bai, Zhi Ding. Blind Source Separation with Given Alphabets Using 8-Approximation Algorithms[J]. Iowa City: Department of Electrical and Computer Engineering,University of Iowa,2001,32(6) :35 -52.

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山西电子技术
2009年 第1期

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