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- W3040474190 abstract "With the advantages of Millimeter wave in wireless communication network, the coverage radius and inter-site distance can be further reduced, the ultra dense network (UDN) becomes the mainstream of future networks. The main challenge faced by UDN is the serious inter-site interference, which needs to be carefully addressed by joint user association and resource allocation methods. In this paper, we propose a multi-agent Q-learning based method to jointly optimize the user association and resource allocation in UDN. The deep Q-network is applied to guarantee the convergence of the proposed method. Simulation results reveal the effectiveness of the proposed method and different performances under different simulation parameters are evaluated." @default.
- W3040474190 created "2020-07-10" @default.
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- W3040474190 date "2020-04-17" @default.
- W3040474190 modified "2023-09-23" @default.
- W3040474190 title "Learning-Based Joint User-AP Association and Resource Allocation in Ultra Dense Network" @default.
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- W3040474190 doi "https://doi.org/10.48550/arxiv.2004.08194" @default.
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