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This paper presents an iterative detection and decoding scheme along with anadaptive strategy to improve the selection of access points (APs) in agrant-free uplink cell-free scenario. With the requirement for the APs to havelow-computational power in mind, we introduce a low-complexity scheme for localactivity and data detection. At the central processing unit (CPU) level, wepropose an adaptive technique based on local log-likelihood ratios (LLRs) toselect the list of APs that should be considered for each device. Simulationresults show that the proposed LLRs-based APs selection scheme outperforms theexisting techniques in the literature in terms of bit error rate (BER) whilerequiring comparable fronthaul load.

Study of Adaptive LLR-based AP selection for Grant-Free Random Access in Cell-Free Networks