Transmit power allocation of energy transmitters for throughput maximisation in wireless powered communication networks. Issue 9 (1st June 2019)

• Record Type: Journal Article
• Authors: Yu, Zhanwei; Chi, Kaikai; Zheng, Kechen; Li, Yanjun; Cheng, Zhen
• Is Part Of: IET communications. Volume 13:Issue 9(2019)
• Page Start: 1200
• Page End: 1206
• Publication Date: 2019-06-01
• Subjects: radiofrequency power transmission -- radio networks -- telecommunication power management -- energy harvesting -- wireless sensor networks -- optimisation; transmit power allocation -- energy transmitters -- wireless powered communication networks -- radio‐frequency energy harvesting -- RF -- promising technologies -- wireless networks -- sinks -- ETs subject -- total power budget -- sum‐throughput maximisation problem -- nonlinear optimisation problem -- sub‐gradient algorithm -- common‐throughput maximisation -- worst node -- CTM problem -- master problem -- linear problem whose optimal solution -- maximal common‐throughput -- throughput unfairness problem -- decreased sum‐throughput; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.6045
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Radio‐frequency (RF) energy harvesting is one promising technology to power the nodes in wireless networks. This study focuses on large‐scale wireless powered communication networks having multiple RF energy transmitters (ETs) and sinks, which almost have not been investigated previously. The authors aim to optimise the throughput via optimizing the transmit power allocation of ETs subject to a total power budget. Specifically, for the sum‐throughput maximisation (STM) problem, they firstly formulate it to be a non‐linear optimisation problem, then prove its convexity and finally propose an efficient dual sub‐gradient algorithm to solve it. Owing to the throughput unfairness among nodes of the STM approach, they further consider the common‐throughput maximisation (CTM; i.e. the worst node's throughput) and propose a very efficient algorithm for it. This algorithm divides the CTM problem into a master problem and a subproblem. The subproblem of determining the feasibility of a given common‐throughput is solved by transforming it to a linear problem whose optimal solution indicates the feasibility. The master problem of determining the maximal common‐throughput is solved by using the bisection search method. Simulation results demonstrate the effectiveness of the CTM approach to mitigate the throughput unfairness problem at the cost of decreased sum‐throughput.