Multi-Agent Reinforcement Learning for Dynamic Topology Optimization of Mesh Wireless Networks

In Mesh Wireless Networks (MWNs), the network coverage is extended by connecting Access Points (APs) in a mesh topology, where transmitting frames by multi-hop routing has to sustain the performances, such as end-to-end (E2E) delay and channel efficiency. Several recent studies have focused on minim...

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Veröffentlicht in:	IEEE transactions on wireless communications 2024-09, Vol.23 (9), p.10501-10513
Hauptverfasser:	Sun, Wei, Lv, Qiushuo, Xiao, Yang, Liu, Zhi, Tang, Qingwei, Li, Qiyue, Mu, Daoming
Format:	Artikel
Sprache:	eng
Schlagworte:	Actor-critic ad hoc wireless network Algorithms Convergence Delay Delays Efficiency Logic gates Machine learning mesh wireless network Multiagent systems Network topologies Network topology reinforcement learning Topology Topology optimization Trajectory Vectors Wireless networks
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