Energy‐efficient resource allocation for device‐to‐device communication with WPT. Issue 3 (1st February 2017)

• Record Type: Journal Article
• Authors: Dai, Haibo; Huang, Yongming; Li, Chunguo; Li, Shidang; Yang, Luxi
• Is Part Of: IET communications. Volume 11:Issue 3(2017)
• Page Start: 326
• Page End: 334
• Publication Date: 2017-02-01
• Subjects: cellular radio -- resource allocation -- radiofrequency power transmission -- energy conservation -- game theory -- learning (artificial intelligence) -- optimisation; robust distributed learning algorithm -- optimisation problem -- Nash equilibrium -- gametheoretic learning approach -- cellular network -- wireless power transfer technique -- WPT -- device‐to‐device communication -- energy‐efficient downlink resource allocation problem; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2015.1192
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, the authors address the downlink resource (subchannels and power) allocation problem for device‐to‐device communication with wireless power transfer technique in a cellular network to improve the energy efficiency (EE). The considered problem is formulated as maximising the weighted EE and is solved by leveraging a game‐theoretic learning approach. Specifically, they first prove that an exact potential game applies to the resource allocation problem and there exists the best Nash equilibrium (NE) which is the optimal solution of the optimisation problem. Then, aiming to this optimisation problem with imperfect information, a robust and distributed learning algorithm is proposed and is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.