Efficient QAM Signal Detector for Massive MIMO Systems via PS-ADMM Approach
Abstract
In this paper, we design an efficient quadrature amplitude modulation (QAM) signal detector for massive multiple-input multiple-output (MIMO) communication systems via the penalty-sharing alternating direction method of multipliers (PS-ADMM). Its main content is as follows: first, we formulate QAM-MIMO detection as a maximum-likelihood optimization problem with bound relaxation constraints. Decomposing QAM signals into a sum of multiple binary variables and exploiting introduced binary variables as penalty functions, we transform the detection optimization model to a non-convex sharing problem; second, a customized ADMM algorithm is presented to solve the formulated non-convex optimization problem. In the implementation, all variables can be solved analytically and in parallel; third, it is proved that the proposed PS-ADMM algorithm converges under mild conditions. Simulation results demonstrate the effectiveness of the proposed approach.
Cite
@article{arxiv.2104.08064,
title = {Efficient QAM Signal Detector for Massive MIMO Systems via PS-ADMM Approach},
author = {Quan Zhang and Jiangtao Wang and Yongchao Wang},
journal= {arXiv preprint arXiv:2104.08064},
year = {2021}
}
Comments
11pages, 17figures. Substantial text overlap with arXiv:2010.06798. The supplementary material is the analysis of the convergence and iteration complexity of DPS-ADMM detector