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TIGHTNESS OF A NEW AND ENHANCED SEMIDEFINITE RELAXATION FOR MIMO DETECTION.

Authors :
CHENG LU
YA-FENG LIU
WEI-QIANG ZHANG
SHUZHONG ZHANG
Source :
SIAM Journal on Optimization. 2019, Vol. 29 Issue 1, p719-742. 24p.
Publication Year :
2019

Abstract

In this paper, we consider a fundamental problem in modern digital communications known as multiple-input multiple-output (MIMO) detection, which can be formulated as a complex quadratic programming problem subject to unit-modulus and discrete argument constraints. Various semidefinite-relaxation-based (SDR-based) algorithms have been proposed to solve the problem in the literature. In this paper, we first show that conventional SDR is generally not tight for the problem. Then, we propose a new and enhanced SDR and show its tightness under an easily checkable condition, which essentially requires the level of the noise to be below a certain threshold. The above results have answered an open question posed by So in [Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'10), SIAM, Philadelphia, PA, 2011, pp. 698-711]. Numerical simulation results show that our proposed SDR significantly outperforms the conventional SDR in terms of the relaxation gap. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10526234
Volume :
29
Issue :
1
Database :
Academic Search Index
Journal :
SIAM Journal on Optimization
Publication Type :
Academic Journal
Accession number :
136148900
Full Text :
https://doi.org/10.1137/17M115075X