Learning-Based Joint Optimization of Transmit Power and Harvesting Time in Wireless-Powered Networks With Co-Channel Interference

被引：22
作者：
Lee, Kisong [1 ]
Lee, Jung-Ryun [2 ]
Choi, Hyun-Ho [3 ]
机构：
[1] Dongguk Univ, Dept Informat & Commun Engn, Seoul 04620, South Korea
[2] Chung Ang Univ, Sch Elect Engn, Seoul 06974, South Korea
[3] Hankyong Natl Univ, Dept Elect Elect & Control Engn, Anseong 17579, South Korea
来源：
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2020年 / 69卷 / 03期
基金：
新加坡国家研究基金会;
关键词：
Neural network; energy efficiency; energy harvesting; time switching; optimization; INFORMATION; ALLOCATION; COMPLEXITY; DESCENT;
D O I：
10.1109/TVT.2020.2972596
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：
In this paper, we consider a wireless-powered network with co-channel interference where the transmitters control their transmit power and receivers harvest wireless energy using a time switching policy. Considering the interference channels among multiple nodes, we jointly optimize the transmit power and energy harvesting time to maximize the energy efficiency of the network. To solve this non-convex optimization problem, we first design an iterative algorithm based on a typical optimization technique, and then, propose a learning algorithm based on a neural network with a proper loss function. Simulation results show that the proposed learning algorithm can achieve a near-optimal energy efficiency with reducing the computational complexity, compared to an iterative algorithm with a suboptimal performance.
引用
收藏
页码：3500 / 3504
页数：5
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