Power Allocation for NOMA-Based Visible Light Communication Systems with DQN

被引：0
|
作者：
Deng, Jiawei [1 ]
Tang, Xuan [1 ]
Wei, Xian [2 ]
Li, Pu [1 ]
Li, Jiaqi [1 ]
Li, Xicong [3 ]
Ghassemlooy, Zabih [3 ]
机构：
[1] East China Normal Univ, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China
[2] East China Normal Univ, Software Engn Inst, Shanghai, Peoples R China
[3] Northumbria Univ, Fac Engn & Environm, Opt Commun Res Grp, Newcastle Upon Tyne, Tyne & Wear, England
来源：
2024 14TH INTERNATIONAL SYMPOSIUM ON COMMUNICATION SYSTEMS, NETWORKS AND DIGITAL SIGNAL PROCESSING, CSNDSP 2024 | 2024年
关键词：
Deep reinforcement learning; NOMA; visible light communication; power allocation; NONORTHOGONAL MULTIPLE-ACCESS;
D O I：
10.1109/CSNDSP60683.2024.10636475
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The spectral efficiency of the visible light communication system can be enhanced by using the non-orthogonal multiple access (NOMA) scheme. In this paper, we propose a deep Q network (DQN) framework-based power allocation scheme that maximizes the sum rate of a NOMA-based cellular VLC network with mobility support. The numerical results indicate that the optimisation process achieves improved performance in terms of sum data rate (SDR) by approximately 8.8, 7, and 4% compared with conventional algorithms, such as fixed power allocation, gain ratio power allocation, and genetic algorithms.
引用
收藏
页码：512 / 517
页数：6
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