LEARNING BASED DYNAMIC CLUSTERING FOR COORDINATED MULTIPOINT TRANSMISSION IN COMMUNICATION NETWORKS

    公开(公告)号:US20240388324A1

    公开(公告)日:2024-11-21

    申请号:US18665732

    申请日:2024-05-16

    Abstract: Coordinated Multipoint (CoMP) transmission is a potential candidate to optimize the performance of a network with added flexibility to serve a UE from multiple Base Stations (BSs). However, the performance gain in CoMP is as good as the dynamic clustering. The existing approaches are applicable for a fixed cluster size, which does not capture time-varying channel conditions and the cost of transmission. Embodiments herein provide a method and system for a learning based dynamic clustering of BSs for a CoMP transmission in communication networks. Herein, a framework for the CoMP transmission in 5th Generation (5G) and beyond networks is disclosed. Further, an optimal user-centric dynamic clustering technique is disclosed for the CoMP with the aim of maximizing the throughput subject to the constraint on the cost of transmission from the CoMP cluster i.e., coordinating set of BSs.

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