Joint Decoding and UE-APs Association for Scalable Cell-Free Systems

User-centric cell-free massive multiple-input multiple-output (UC CF mMIMO) is a key technology for 6G. In UC CF mMIMO each user equipment (UE) is jointly served by a small subset of a large set of cooperating access points (APs). The APs are connected through the fronthaul to a central unit (CU) for joint processing. The key to efficiency is the UE-APs association procedure together with the APs/CU cooperative signal decoding. The first is essential for reducing fronthaul signaling and the latter for removing interference. In this work, we design an algorithm to jointly perform UE-APs association and decoding. The aim is to maximize the mean squared error (MSE) between transmitted and CU decoded data, considering the fronthaul data rate limitations. In our approach, the two aspects are jointly considered, allowing improved performance while keeping the amount of fronthaul signaling low. Furthermore, the proposed method has low-complexity, requiring only the knowledge of a signal quality indicator of each UE at the CU to perform joint decoding and UE-APs association. The numerical results have shown that there is a tradeoff between performance and fronthaul requirements, where the proposed method with fewer APs may achieve the same bit error rate (BER) performance in comparison to conventional CF systems where each AP serves all UEs.