DocumentCode :
1525485
Title :
Enhancing the Performance of the SIC-MMSE Iterative Receiver for Coded MIMO Systems via Companding
Author :
Dai, Xiaoming
Author_Institution :
Datang Wireless Mobile Innovation Center, China Acad. of Telecommun. Technol., Beijing, China
Volume :
16
Issue :
6
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
921
Lastpage :
924
Abstract :
Iterative detection and decoding (IDD) method based on soft interference cancellation and minimum-mean squared-error filtering (SIC-MMSE) has received considerable attention in recent years due to its good performance-complexity tradeoff for coded multiple-input multiple-output (MIMO) systems. The Gaussianity of the a priori and a posteriori log-likelihood ratios (LLRs) computed at the constitute stages of the SIC-MMSE iterative receiver is a presumption for IDD to work. In this letter, the Gaussianity assumption is first shown to be not tight for high rate coded MIMO systems and thus leads to poor performance (for high rate coded MIMO systems). Then a non-linear companding based transformation method is incorporated into the SIC-MMSE iterative receiver to alleviate the non-Gaussianity of the a priori and a posteriori LLRs due to the imperfection of the (high-rate) code and per-stream approximation. Analytical and numerical results show that the proposed transformed SIC-MMSE iterative receiver achieves significant performances gains over the conventional one for coded MIMO systems, in particular, high rate coded ones with even lower computational complexity.
Keywords :
Gaussian processes; MIMO communication; filtering theory; interference suppression; iterative decoding; least mean squares methods; maximum likelihood detection; radio receivers; Gaussianity assumption; IDD; MMSE filtering; SIC; a posteriori log likelihood ratio; a priori log likelihood ratio; coded MIMO system; iterative decoding; iterative detection; iterative receiver; minimum mean squared error; multiple input multiple output; nonGaussianity; nonlinear companding based transformation; per-stream approximation; soft interference cancellation; Channel estimation; Decoding; Interference; Iterative decoding; MIMO; Multiplexing; Receivers; Companding; iterative detection and decoding (IDD); soft interference cancellation and minimum-mean squared-error filtering (SIC-MMSE);
fLanguage :
English
Journal_Title :
Communications Letters, IEEE
Publisher :
ieee
ISSN :
1089-7798
Type :
jour
DOI :
10.1109/LCOMM.2012.042512.120618
Filename :
6205425
Link To Document :
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