An efficient location-based pilot assignment in Cell-Free Massive MIMO

Abstract

Cell-free Massive multiple-input multiple-output can offer many degrees of freedom for the high data rate and coverage probability. This network topology is one of the cutting-edge technologies potentially applied for next-generation wireless communications. In the canonical structure, however, each access point needs to accurately estimate the channel state information for the signal detection in the uplink and the precoding design in the downlink. Due to the finite lengths of coherence intervals, pilot contamination is one of the bottlenecks, reducing the data throughput of each user. We propose an efficient pilot assignment scheme called location-based pilot assignment (LPA) to overcome this limitation. It takes full advantage of the number of orthogonal pilot signals into account. The proposed algorithm divides the coverage area into smaller areas based on the number of users, where each area uses a subset of the pilot signals. Numerical results show that the proposed pilot assignment, LPA, offers good spectral efficiency to every users in the network with a tolerable computational complexity.