Clustering Algorithm Based on Many-to-Many Matching in Heterogeneous Cloud Radio Access Network

Abstract

Coordinated Multiple Points (CoMP) is proposed to improve the performance of cellular communication systems further. While improper base station selection may hurt network performance, building an appropriate base station cluster for users is essential. However, many current methods will damage edge users’ Quality of Service (QoS) while increasing the total system throughput; hence, fairness between users cannot be guaranteed. In this paper, based on the theoretical basis of many-to-many matching, we have defined the preference list of users and base stations and described the exchange matching conditions, matching blocking pairs, and stable matching. While ensuring the overall quality of service fairness of users, we can help each user find the best number of service base stations as much as possible to improve the system’s total throughput. The simulation results show that, compared with the distance-based clustering algorithm and Reference Signal Receiving Power (RSRP) based clustering algorithm, our proposed method increases the total system throughput by 12%, and more than 88.56% of users reach the average system throughput.