Throughput Maximization of Wireless-Powered Communication Network With Mobile Access Points

计算机科学 能源消耗 吞吐量 计算机网络 能量收集 能量(信号处理) 传输(电信) 无线 实时计算 电信 电气工程 数学 统计 工程类
作者
Xiaoying Liu,Bin Xu,Kechen Zheng,Haifeng Zheng
出处
期刊:IEEE Transactions on Wireless Communications [Institute of Electrical and Electronics Engineers]
卷期号:22 (7): 4401-4415 被引量:57
标识
DOI:10.1109/twc.2022.3225085
摘要

In order to mitigate thedouble near-far effect, we focus on a mobile wireless-powered communication network (WPCN), where sensor nodes harvest energy from the radio frequency (RF) signal of the mobile energy access point (EAP), and transmit data to the mobile data access point (DAP) by using the harvested energy. Only the sensor nodes with energy larger than a threshold, which is mainly determined by the energy consumption of one transmission, have opportunities to transmit data. Due to the mobility of the EAP and DAP, the distance between the EAP and DAP changes over time. When the DAP moves into the operation region of the EAP, the EAP and DAP could not work simultaneously due to the severe interference, and an energy harvesting probability is employed to denote the probability that the EAP works in this scenario. The purpose of this paper is to identify the optimal transmission policy, i.e., the optimal pairing of the energy consumption of one transmission and the energy harvesting probability, that maximizes the throughput of the WPCN under an energy causality constraint. By analyzing the energy causality constraint, we show that the WPCN could be divided into an energy-sufficient state and an energy-limited state by the pairing of the energy consumption of one transmission and the energy harvesting probability. Since the energy consumption of one transmission and the energy harvesting probability are jointly intertwined with the energy causality constraint, making the joint optimization problem intractable, we divide the throughput maximization problem into two layers. In the inner problem, we investigate the optimal energy consumption of one transmission with a given energy harvesting probability. In the outer problem, we derive the optimal energy harvesting probability based on the obtained optimal energy consumption of one transmission. According to the aforementioned investigations, we propose a two-layer algorithm to obtain the specific solution. Numerical results are conducted to validate the theoretical results and the efficiency of the proposed two-layer algorithm.
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