Energy cooperation in multi‐user wireless‐powered relay networks. Issue 11 (1st July 2015)

• Record Type: Journal Article
• Authors: Yang, Dingcheng; Zhou, Xiaoxiao; Xiao, Lin; Wu, Fahui
• Is Part Of: IET communications. Volume 9:Issue 11(2015)
• Page Start: 1412
• Page End: 1420
• Publication Date: 2015-07-01
• Subjects: relay networks (telecommunication) -- cooperative communication -- energy harvesting -- telecommunication power supplies -- amplify and forward communication -- decode and forward communication -- concave programming -- convex programming -- iterative methods -- radio networks; multiuser wireless‐powered relay networks -- energy cooperation schemes -- wireless cooperative networks -- energy harvesting relay -- power splitting scheme -- received signal -- amplify‐and‐forward modes -- decode‐and‐forward modes -- energy cooperation optimisation problem -- nonconvex optimisation problem -- convex problems -- local optimum -- iterative energy cooperation solution; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2014.1100
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, energy cooperation schemes are considered in wireless cooperative networks; in these networks multiple pairs of users communicate with each other, assisted by an energy harvesting relay that gathers energy from the received signal by applying a power splitting scheme and forwards the received signal by using the harvested energy. This study is focused on the energy cooperation strategies for the relay to distribute the harvested energy between the multiple user pairs in amplify‐and‐forward and in decode‐and‐forward modes. Specifically, optimal solutions without energy cooperation at the relay node are first proposed and then the authors formulate the energy cooperation optimisation problem. This optimisation problem is non‐convex. They propose an iterative energy cooperation solution to maximise the system throughput by assigning the proper harvested energy to each user pair for both types of forwarding models. They show that with the proposed method, the update in each iteration consists of a group of convex problems with a continuous parameter. Moreover, they derive the optimal solution to these convex problems in closed‐form and it is shown that the solution can converge to a local optimum. Simulation results demonstrate that the proposed algorithm outperforms the traditional non‐cooperation method.