Deep Q-Network Learning Based Downlink Resource Allocation for Hybrid RF/VLC Systems

Developing high data rate systems to meet the requirements of fifth generation mobile systems has become crucial. Hybrid radio frequency/visible light communication (RF/VLC) has appeared as a promising mechanism for achieving this objective. In hybrid RF/VLC, data rate maximization is subject to con...

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Vydáno v:	IEEE access Ročník 8; s. 1
Hlavní autoři:	Shrivastava, Shivanshu, Chen, Bin, Chen, Chen, Wang, Hui, Dai, Mingjun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Access Points Achievable sum-rate Algorithms Bandwidth Bandwidths Data models Deep Q-Network (DQN) Learning Downlink Hybrid power systems Hybrid RF/VLC Hybrid systems Machine learning Maximization Mobile communication systems Multilayers Optical communication Optimization Optimization algorithms Power Radio frequency Radio Frequency (RF) Resource allocation Resource management User Association User Equipment Visible Light Communication (VLC)
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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