This is a code package for the following scientific article:
Jianan Bai and Erik G. Larsson, "Activity detection in distributed MIMO: Distributed AMP via likelihood ratio fusion," IEEE Wireless Communications Letters, to appear, doi: 10.1109/LWC.2022.3197053.
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.
This work was supported in part by ELLIIT, the KAW foundation, and the European Union’s Horizon 2020 research and innovation program under grant agreement no. 101013425 (REINDEER).
We use the implementation of covariance-based approach from https://github.com/emilbjornson/grant-free.
This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.