Centralized and Distributed Deep Reinforcement Learning Methods for Downlink Sum-Rate Optimization

For a multi-cell, multi-user, cellular network downlink sum-rate maximization through power allocation is a nonconvex and NP-hard optimization problem. In this article, we present an effective approach to solving this problem through single- and multi-agent actor-critic deep reinforcement learning (...

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Veröffentlicht in:	IEEE transactions on wireless communications 2020-12, Vol.19 (12), p.8410-8426
Hauptverfasser:	Khan, Ahmad Ali, Adve, Raviraj S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cellular communication Deep learning Deep reinforcement learning Downlink Downlinking Information exchange Machine learning Mathematical programming Multiagent systems Optimization Resource management sum-rate maximization Supervised learning Wireless communication
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