English

Multiuser Detection by MAP Estimation with Sum-of-Absolute-Values Relaxation

Information Theory 2015-10-27 v1 math.IT

Abstract

In this article, we consider multiuser detection that copes with multiple access interference caused in star-topology machine-to-machine (M2M) communications. We assume that the transmitted signals are discrete-valued (e.g. binary signals taking values of ±1\pm 1), which is taken into account as prior information in detection. We formulate the detection problem as the maximum a posteriori (MAP) estimation, which is relaxed to a convex optimization called the sum-of-absolute-values (SOAV) optimization. The SOAV optimization can be efficiently solved by a proximal splitting algorithm, for which we give the proximity operator in a closed form. Numerical simulations are shown to illustrate the effectiveness of the proposed approach compared with the linear minimum mean-square-error (LMMSE) and the least absolute shrinkage and selection operator (LASSO) methods.

Keywords

Cite

@article{arxiv.1510.07273,
  title  = {Multiuser Detection by MAP Estimation with Sum-of-Absolute-Values Relaxation},
  author = {Hampei Sasahara and Kazunori Hayashi and Masaaki Nagahara},
  journal= {arXiv preprint arXiv:1510.07273},
  year   = {2015}
}

Comments

submitted; 6 pages, 7 figures

R2 v1 2026-06-22T11:28:24.534Z