We develop a new algorithm for activity detection for grant-free multiple access in distributed multiple-input multiple-output (MIMO). The algorithm is a distributed version of the approximate message passing (AMP) based on a soft combination of likelihood ratios computed independently at multiple access points. The underpinning theoretical basis of our algorithm is a new observation that we made about the state evolution in the AMP. Specifically, with a minimum mean-square error denoiser, the state maintains a block-diagonal structure whenever the covariance matrices of the signals have such a structure. We show by numerical examples that the algorithm outperforms competing schemes from the literature.
@article{arxiv.2208.03070,
title = {Activity Detection in Distributed MIMO: Distributed AMP via Likelihood Ratio Fusion},
author = {Jianan Bai and Erik G. Larsson},
journal= {arXiv preprint arXiv:2208.03070},
year = {2022}
}
Comments
5 pages, 2 figures. This paper has been accepted for publication in IEEE Wireless Communications Letters. Code available at https://github.com/jiananbai/distributed-AMP