This paper presents an iterative detection and decoding scheme along with an adaptive strategy to improve the selection of access points (APs) in a grant-free uplink cell-free scenario. With the requirement for the APs to have low-computational power in mind, we introduce a low-complexity scheme for local activity and data detection. At the central processing unit (CPU) level, we propose an adaptive technique based on local log-likelihood ratios (LLRs) to select the list of APs that should be considered for each device. Simulation results show that the proposed LLRs-based APs selection scheme outperforms the existing techniques in the literature in terms of bit error rate (BER) while requiring comparable fronthaul load.
@article{arxiv.2312.16781,
title = {Study of Adaptive LLR-based AP selection for Grant-Free Random Access in Cell-Free Networks},
author = {R. Di Renna and R. C. de Lamare},
journal= {arXiv preprint arXiv:2312.16781},
year = {2023}
}