Title :
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
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;
Conference_Titel :
Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of
Conference_Location :
Eilat
Print_ISBN :
978-1-4673-4682-5
DOI :
10.1109/EEEI.2012.6376987
