Mutual Information Optimization for Cell-Free Massive MIMO with Sequential Limited-Rate Fronthaul

Cell-Free massive multiple-input multiple-output (mMIMO) is an emerging technology that promises to upgrade the majority of wireless communication networks’ features. That can be accomplished thanks to its ubiquitous architecture, which overcomes inter-cell interference limitations, provides additional macro-diversity and ensures that every user is always surrounded by a sufficient number of access points (APs). The present paper studies the uplink scenario of a cell-free mMIMO setup that utilizes a finite-capacity radio stripe as its fronthaul (FH) network. By exploiting the consecutively connected topology of the antenna processing units (APUs), we derive and optimize, subject to the radio stripe’s finite-capacity links, the entire system’s end-to-end mutual information (MI), in the presence of channel estimation errors and compression noise. Both of the aforementioned objectives are accomplished sequentially, using only local information and information acquired from all previous steps of the proposed algorithm. The numerical results showcase that, even under uplink sequential processing and FH rate constraints, the proposed scheme can achieve a much higher sum throughput than the standard sequential linear MMSE approach.