Dynamic Fronthaul Load Optimization for Uplink Scalable Cell-Free User-Centric Massive MIMO

This study investigates scalable uplink cell-free massive multiple-input multiple-output networks, comprising user equipments (UEs), radio units (RUs), data routers, and decentralized processing units (DUs). In our model, UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors, implementing the physical layer for each user, are hosted as software-defined virtual network functions by the DUs. In our paradigm, RUs, data routers, and DUs are not fully connected, necessitating a holistic approach to address the joint challenges of cluster processor placement (at one of the DUs) and the allocation of fronthaul data links among RUs, routers, and DUs. We simultaneously consider the fronthaul topology, the limited fronthaul communication capacity, and computation constraints at the DUs. Specifically, we formulate the joint optimization of fronthaul load balancing and cluster processor placement as a mixed-integer linear problem. Furthermore, we present numerical results that shed light on the interplay between these elements under finite resolution of the A/D quantization at the RUs.