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YS Nasir, D Guo
Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks
IEEE Journal on Selected Areas in Communications (Impact Factor 9.302), vol. 37, no. 10, pp. 2239 - 2250, 2019; doi: 10.1109/JSAC.2019.2933973
[BibTeX]
[IEEEXplore]
@article{nasir2019multi, author={Y. S. {Nasir} and D. {Guo}}, journal={IEEE Journal on Selected Areas in Communications}, title={Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks}, year={2019}, volume={37}, number={10}, pages={2239-2250}, keywords={control engineering computing;learning (artificial intelligence);MIMO communication;multi-agent systems;optimisation;power control;quality of service;radio networks;radiofrequency interference;resource allocation;telecommunication computing;telecommunication control;wireless channels;wireless networks;transmit power control;near-optimal power allocation;challenging optimization problem;instantaneous cross-cell channel state information requirement;distributively executed dynamic power allocation scheme;model-free deep reinforcement learning;weighted sum-rate utility function;maximum sum-rate;deep Q-learning;typical network architecture;delayed CSI measurements;CSI delay;multiagent deep reinforcement;quality of service information;proportionally fair scheduling;real time;Resource management;Transmitters;Receivers;Fading channels;Dynamic scheduling;Power control;Heuristic algorithms;Deep Q-learning;radio resource management;interference mitigation;power control;Jakes fading model}, doi={10.1109/JSAC.2019.2933973}, ISSN={}, month={Oct},}
YS Nasir, D Guo
Deep reinforcement learning for distributed dynamic power allocation in wireless networks
arXiv preprint arXiv:1808.00490, Aug. 2018
[BibTeX]
[PDF]
@article{nasir2018deep, title={Deep reinforcement learning for distributed dynamic power allocation in wireless networks}, author={Nasir, Yasar Sinan and Guo, Dongning}, journal={arXiv preprint arXiv:1808.00490}, year={2018}}