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Volume 30 Issue 7
Jan.  2011
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Xu Xin, Cai Yue-ming, Xu You-yun. Soft Semi-definite Relaxation for Detection of 16-QAM Signaling in MIMO Systems[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1651-1654. doi: 10.3724/SP.J.1146.2006.01828
Citation: Xu Xin, Cai Yue-ming, Xu You-yun. Soft Semi-definite Relaxation for Detection of 16-QAM Signaling in MIMO Systems[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1651-1654. doi: 10.3724/SP.J.1146.2006.01828

Soft Semi-definite Relaxation for Detection of 16-QAM Signaling in MIMO Systems

doi: 10.3724/SP.J.1146.2006.01828
  • Received Date: 2006-11-20
  • Rev Recd Date: 2007-07-12
  • Publish Date: 2008-07-19
  • In this paper, soft semi-definite relaxation for detection of 16-QAM signaling in MIMO systems is investigated. Additional constraints and dimension-reduction approximation method are proposed, which can be used to calculate the Log-Likelihood Ratio (LLR) and reduce dimensions of the SDR detection, respectively. Simulations show that the soft SDR detector exhibits a better performance in a flat-fading MIMO channels, and the complexity of the soft detector is considerably reduced by reducing the dimensions of the SDR programming, but the performance loss leads by dimension reduction is about 0.2 to 0.4 dB.
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  • Ma W K, Davidson T N, Wong K M, Luo Z Q, and Ching PC. Quasi-maximum-likelihood multiuser detection usingsemi-definite relaxation with application to synchronousCDMA[J].IEEE Trans. on Signal Processing.2002, 50(4):912-922[2]Windpassinger C. Detection and precoding for multipleinputmultiple-output channels. [PhD Dissertation], ErlangenUniversity, 2004.[3]Helmberg C, Rendl F, Vanderbei R J, and Wolkowicz H. Aninterior point method for semi-definite programming[J].SIAM J.Optim.1996, 6(2):342-361[4]Wiesel Y C E A and Shamai S. Semidefinite relaxation fordetection of 16-QAM signaling in mimo channels[J].IEEESignal Processing Letters.2005, 12(9):653-656[5]Steingrimsson B, Zhi-Quan Luo, and Wong K M. Softquasi-maximum-likelihood detection for multiple-antennawireless channels[J].IEEE Trans. on Signal Processing.2003,51(11):2710-2719[6]Hochwald B M and Brink S T. Achieving near-capacity on amultiple-antenna channel[J].IEEE Trans. on Commun.2003,51(3):389-399[7]Sturm J. Using sedumi 1.02, a matlab toolbox foroptimization over symmetric cones. Optimization Methodsand Software, 1999, 11(12): 625-653.[8]Lberg Johan. YALMIP: A toolbox for modeling andoptimization in MATLAB. IEEE International Symposiumon Computer Aided Control Systems Design, Taipei, Taiwan,Sept. 2-4, 2004: 284-289.
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