Energy provision minimisation in large-scale wireless powered communication networks with throughput demand

被引:1
作者
Ge, Haijiang [1 ,2 ]
Yu, Zhanwei [1 ]
Chi, Kaikai [1 ]
Mao, Keji [1 ]
Shao, Qike [1 ]
Chen, Lijian [1 ]
机构
[1] Zhejiang Univ Technol, Sch Comp Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China
[2] Hangzhou Vocat & Tech Coll, Inst Informat Engn, Hangzhou 310018, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
inductive power transmission; linear programming; optimisation; cooperative communication; convex programming; distributed algorithms; resource allocation; efficient dual subgradient algorithm; optimal transmit power; throughput unfairness problem; increased energy provision; total energy provision; energy provision reduction percentage; ETs increases; energy provision minimisation; wireless powered communication networks; single radio-frequency energy transmitter; single sink; multiple ETs; available power provision; data collection schemes; multiple RF ETs; transmit power allocation; large-scale WPCNs; node-throughput demand case; convex optimisation problem; linear programming problem; sum-throughput demand case; nonlinear optimisation problem; RESOURCE-ALLOCATION; MAXIMIZATION; SWIPT;
D O I
10.1049/iet-com.2019.0022
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
So far, the research of wireless powered communication networks (WPCNs) mainly considers the scenarios with a single radio-frequency (RF) energy transmitter (ET) and a single sink. However, in practice, there are many applications where multiple ETs and sinks need to be deployed. This study focuses on large-scale WPCNs having multiple RF ETs and sinks. Specifically, the authors aim to minimise the total energy provision by optimising ETs' transmit powers with the node-throughput demand and sum-throughput demand, respectively. For the node-throughput demand case, they firstly formulate it to be a convex optimisation problem, then transform it to be a linear programming (LP) problem, and finally present a distributed algorithm to obtain the optimal solution. For the sum-throughput demand case, they firstly formulate it to be a non-linear optimisation problem, then prove its convexity and finally propose an efficient dual subgradient algorithm to obtain the optimal solution. Simulation results demonstrate that compared to the sum-throughput demand, imposing the node-throughput demand can effectively alleviate the throughput unfairness at the cost of increased energy provision; the proposed optimal algorithms can substantially decrease the total energy provision of ETs; the energy provision reduction percentage achieved by their schemes increases as the number of ETs increases.
引用
收藏
页码:458 / 465
页数:8
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