Hybrid Centralized-Distributed Resource Allocation Based on Deep Reinforcement Learning for Cooperative D2D Communications

Device-to-device (D2D) technology enables direct communication between adjacent devices within cellular networks. Due to its high data rate, low latency, and performance improvement in spectrum and energy efficiency, it has been widely investigated and applied as a critical technology in 5G New Radi...

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Veröffentlicht in:	IEEE access Jg. 12; S. 196609 - 196623
Hauptverfasser:	Yu, Yang, Tang, Xiaoqing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Cellular communication Cellular networks Clean energy Communication Cooperative communication Cooperative control Copper Deep learning deep reinforcement learning Device-to-device communication Distributed processing Energy efficiency Graph matching Graph theory Heuristic algorithms Interference Mathematical programming Mixed integer Network latency Optimization Power control Power management Relays Resource allocation Resource management Signaling Spectrum allocation Sustainable development Wireless communication
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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