Likelihood Ascent-Gibbs Sampling for Efficient MIMO Detection

被引：0
|
作者：
Anil, K. K. [1 ]
Raju, A. K. [1 ]
Snehith, T. C. [1 ]
Ramanathan, R. [1 ]
机构：
[1] Amrita Vishwa Vidyapeetham, Dept Elect & Commun Engn, Coimbatore 641112, Tamil Nadu, India
来源：
2015 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC) | 2015年
关键词：
Mixed Gibbs Sampling; Likelihood Ascent Search; Channel Estimation Error; MIMO detection;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Gibbs Sampling (LAS-MGS) for effective detection with channel estimation error. We analyze its performance in the presence of channel estimation error for 2x 2 and 4x4 MIMO systems employing BPSK modulation scheme. At low SNRs, performance of ZF-MGS and LAS-MGS is similar but at high SNRs, LAS-MGS performs significantly better. LAS-MGS outperforms conventional Mixed Gibbs Sampling (MGS) and we are able to harness similar gain even with channel estimation errors. We conclude that LAS-MGS is a worthy candidate for further research.
引用
收藏
页码：598 / 602
页数：5
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