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The network-assisted full-duplex (NAFD) system realizes flexible duplex in the spatial domain within the same time-frequency resource. With the explosive growth of the number of users and remote antenna units (RAUs) under 6G scenario, the resource utilization of the system is lower. When the resource of users is selected by the RAUs to send or receive, collisions or congestion may occur due to mechanisms such as grant-free. Aiming at making better use of system resources, a load-aware dynamic mode selection scheme with NAFD scheme is proposed to improve the access efficiency and resource utility of the system. This paper first propose a centralized Q-learning algorithm which determines a clever strategy to approach the ultimate goal by itself and excels in environment dynamics. However, the size of the Q-table used in the centralized Q-learning algorithm for storage is huge. Further, a distributed multi-agent Q-learning algorithm is proposed which has a smaller size of Q-table and lower complexity to suit for actual scenarios. The simulation results showed that the proposed load-aware dynamic mode selection scheme can significantly improve resource utility and throughput performance than other traditional schemes.

Load-Aware Dynamic Mode Selection for Network-Assisted Full-Duplex Cell-Free Large-Scale Distributed MIMO Systems