Reinforcement Learning-Based Joint User Scheduling and Link Configuration in Millimeter-Wave Networks

In this paper, we develop algorithms for joint user scheduling and three types of mmWave link configuration: relay selection, codebook optimization, and beam tracking in millimeter wave (mmWave) networks. Our goal is to design an online controller that dynamically schedules users and configures thei...

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Veröffentlicht in:	IEEE transactions on wireless communications 2023-05, Vol.22 (5), p.3038-3054
Hauptverfasser:	Zhang, Yi, Heath, Robert W.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms beam tracking codebook selection Complexity Configurations Control systems design Decision making Deep learning deep reinforcement learning Delay Delays Dynamic scheduling Machine learning Millimeter wave Millimeter wave communication Millimeter waves mobility multi-armed bandit Multi-armed bandit problems Neural networks Optimization proximal policy optimization relay selection Relays Scheduling Thompson sampling Training user scheduling Wireless communication
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