Designing a QAM Signal Detector for Massive Mimo Systems via PS-ADMM Approach

Quan Zhang; Xuyang Zhao; Jiangtao Wang; Yongchao Wang

ICASSP 2022accepted0 citations

Designing a QAM Signal Detector for Massive Mimo Systems via PS-ADMM Approach

Quan Zhang, Xuyang Zhao, Jiangtao Wang, Yongchao Wang

Abstract

This paper presents 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). The content of the paper is summarized 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.

BibTeX

@inproceedings{icassp2022_designingaqamsig,
  title = {Designing a QAM Signal Detector for Massive Mimo Systems via PS-ADMM Approach},
  author = {Quan Zhang and Xuyang Zhao and Jiangtao Wang and Yongchao Wang},
  booktitle = {ICASSP 2022},
  year = {2022}
}