Energy provision minimisation in large‐scale wireless powered communication networks with throughput demand. Issue 3 (1st February 2020)

• Record Type: Journal Article
• Authors: Ge, Haijiang; Yu, Zhanwei; Chi, Kaikai; Mao, Keji; Shao, Qike; Chen, Lijian
• Is Part Of: IET communications. Volume 14:Issue 3(2020)
• Page Start: 458
• Page End: 465
• Publication Date: 2020-02-01
• Subjects: 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; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.0022
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : 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.