Pilot Assignment for Cell-Free Massive MIMO: A Spectral Clustering Approach

In this letter, we study the pilot assignment scheme in the uplink cell-free massive multiple-input multiple-output system. To accurately depict the potential co-pilot interference (CPI) among the user terminals (UTs), we introduce the normalized contribution value of AP to the received signal strength at the UT. A weighted conflict clustering graph is constructed by using the potential CPI to define the weight of the edge that connects the co-pilot UTs. Then, the pilot assignment optimization is transformed into a Min-Cut problem, which is further converted as a more effective normalized cut to find a partition of the UTs into disjoint clusters for minimizing the overall CPI. We develop a two-stage algorithm via spectral clustering to solve the relaxed problem efficiently. Numerical results are provided to validate the superiority of the proposed algorithm as compared to the existing methods in terms of the uplink average sum-rate and the quality of channel estimation.