Pilot-based clustering method in multi-ARS cell-free MIMO systems

Cell Free (CF) model, with the advantages of improved performance, high load capacity, and uniform communication quality, is a potential solution for 5G and B5G networks. Furthermore, the combination of the CF and advanced Unmanned Aerial Vehicle (UAV) technology further enhances the overall service quality and flexibility of the system. In this work, we examine the Multi-ARS CF model, where a large number of UAVs acting as Aerial Relay Stations (ARSs) are coordinated by the Ground Base Station (GBS) and cooperate to serve a large number of Mobile Stations (MSs) within the same frequency and time resources. The communication protocol utilizes the time division duplex (TDD) mechanism, with the implementation of the Minimum Mean Square Error (MMSE) method for estimating the uplink channel. A closed-form expression for MS throughput is derived. Moreover, we propose a pilot assignment algorithm at the master ARSs focusing on minimizing “pilot contamination” in the MS-master ARS communication link. Additionally, a clustering algorithm based on pilots is implemented. The system’s performance is assessed through the Cumulative Distribution Function (CDF) of the MS throughput and compared with other pilot assignment algorithms, such as random and the Greedy algorithm. The results reveal that the pilot assignment and clustering algorithm successfully address the pilot contamination issue and enhance the overall system performance.