Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks - researchr publication related

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Mohamed Sana, Antonio De Domenico, Wei Yu 0001, Yves Lostanlen, Emilio Calvanese Strinati. Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks. IEEE Transactions on Wireless Communications, 19(10):6520-6534, 2020. [doi]

The following publications are possibly variants of this publication:

Multi-Agent Deep Reinforcement Learning Based User Association for Dense mmWave NetworksMohamed Sana, Antonio De Domenico, Emilio Calvanese Strinati. globecom 2019: 1-6 [doi]

Multi-Agent Deep Reinforcement Learning for Joint Decoupled User Association and Trajectory Design in Full-Duplex Multi-UAV NetworksChen Dai, Kun Zhu 0001, Ekram Hossain 0001. tmc, 22(10):6056-6070, October 2023. [doi]

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