Implementation of quasi-maximum-likelihood detection based on semidefinite relaxation and linear programming

Author

Rapoport, Lev ; Yanxing, Zeng ; Ivanov, Vladimir ; Jianqiang, Shen

Author_Institution

Russian R&D Center, Huawei Technol. Co., Ltd., Moscow, Russia

fYear

2012

fDate

14-17 Nov. 2012

Firstpage

1

Lastpage

5

Abstract

In this paper, a new numerical method is proposed for fast signal detection in large scale MIMO systems. Semidefinite relaxation (SDR) approach is utilized. The SDR problem is further reduced to the sequential linear programming by adding new form of cutting planes and column generation method. Bit error rate (BER) performance results conclude the paper. BER performance is compared with other MIMO detection algorithms. Performance of the new scheme practically identical to performance of the maximum-likelihood detection, while complexity is much less and does not depend on the conditioning number of the channel matrix.

Keywords

MIMO communication; error statistics; linear programming; maximum likelihood detection; relaxation theory; wireless channels; BER; SDR approach; bit error rate; channel matrix conditioning; column generation method; cutting plane form; large scale MIMO detection system; numerical method; quasimaximum-likelihood detection; semidenite relaxation programming; sequential linear programming; signal detection; Bit error rate; Complexity theory; Linear matrix inequalities; Linear programming; Optimization; Symmetric matrices; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of

Conference_Location

Eilat

Print_ISBN

978-1-4673-4682-5

Type

conf

DOI

10.1109/EEEI.2012.6376987

Filename

6376987