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

Abstract

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.

Next Generation Multiple Access with Cell-Free Massive MIMO

“…2) Future research directions: ML-based algorithms can be utilized in NAFD CF-mMIMO networks to reduce the complexity of the joint AP mode assignment and AP clustering in UC scenarios. Zhu et al [264] proposed a loadaware dynamic mode selection scheme for the APs, aiming to maximize the UL-DL sum-rate of the network while considering the per-user traffic load. They investigated both centralized Q-learning and distributed multi-agent Q-learning algorithms with varying complexities, demonstrating that the former is more suitable for real-world applications due to its smaller storage unit and lower complexity.…”

Next Generation Multiple Access with Cell-Free Massive MIMO

“…2) Future research directions: ML-based algorithms can be utilized in NAFD CF-mMIMO networks to reduce the complexity of the joint AP mode assignment and AP clustering in UC scenarios. Zhu et al [264] proposed a loadaware dynamic mode selection scheme for the APs, aiming to maximize the UL-DL sum-rate of the network while considering the per-user traffic load. They investigated both centralized Q-learning and distributed multi-agent Q-learning algorithms with varying complexities, demonstrating that the former is more suitable for real-world applications due to its smaller storage unit and lower complexity.…”

Network-Assisted Full-Duplex Enabled Ultrareliable and Low-Latency Communications

“…Latency for the control plane will be greatly reduced while still guarantee the access reliability. We have studied load-aware dynamic mode selection for NAFD scheme [17]. Intelligent reinforcement learning algorithms are proposed which proved that NAFD scheme enabled cell-free massive MIMO system with appropriately scheduled APs is a promising solution to meet the heterogeneous traffic loads in next generation wireless systems.…”