Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks
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We consider a user-centric scalable cell-free massive MIMO network with a total of LM distributed remote radio unit antennas serving K user equipments (UEs). Many works in the current literature assume LM≫ K, enabling high UE data rates but also leading to a system not operating at its maximum performance in terms of sum throughput. We provide a new perspective on cell-free massive MIMO networks, investigating rate allocation and the UE density regime in which the network makes use of its full capability. The UE density K approximately equal to LM/2 is the range in which the system reaches the largest sum throughput. In addition, there is a significant fraction of UEs with relatively low throughput, when serving K>LM/2 UEs simultaneously. We propose to reduce the number of active UEs per time slot, such that the system does not operate at “full load”, and impose throughput fairness among all users via a scheduler designed to maximize a suitably defined concave componentwise non-decreasing network utility function. Our numerical simulations show that we can tune the system such that a desired distribution of the UE throughput, depending on the utility function, is achieved.
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