Resource allocation strategy against selfishness in cognitive radio ad‐hoc network based on Stackelberg game. Issue 13 (1st August 2019)

• Record Type: Journal Article
• Authors: Liu, Zhixin; Zhao, Mingye; Chan, Kit Yan; Liu, Yang; Ma, Kai
• Is Part Of: IET communications. Volume 13:Issue 13(2019)
• Page Start: 1962
• Page End: 1970
• Publication Date: 2019-08-01
• Subjects: game theory -- cognitive radio -- cooperative communication -- resource allocation -- ad hoc networks; resource allocation strategy -- selfishness -- cognitive radio -- ad‐hoc network -- Stackelberg game -- CRAHN -- spectrum resource -- selfish nodes -- unfair resource competition -- incentive strategy -- secondary‐user -- SU -- primary‐user -- PU -- spectrum leasing mode -- common authorised spectrum usage time -- selfish tendency -- relay task -- selfish behaviour -- evaluation coefficient; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.5166
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Although the Cognitive Radio Ad‐Hoc Network (CRAHN) is an effective technology to fully utilize the spectrum resource, the appearance of selfish nodes seriously reduces the communication efficiency of CRAHN and generates unfair resource competition. In this paper, a new incentive strategy is proposed to tackle selfish nodes in CRAHN. In our CRAHN model, the Secondary‐User (SU) cooperates with the Primary‐User (PU) in a spectrum leasing mode. Since PU can select multiple SUs as relays but only leases a common authorized spectrum usage time to SUs, the SU has the selfish tendency to reduce its power in relay task, which seriously damage the partnership between PU and SUs. We propose an evaluation coefficient to evaluate the behavior of each SU, where the evaluation coefficient establishes the reward and punishment mechanism to suppress the selfish behavior of SU in relay task. Meanwhile, in order to solve resource allocation problem, a Stackelberg game between PU and SUs is formulated and the optimal solutions are determined in a distributed manner. Simulation results validate that the incentive strategy can effectively suppress the selfish behavior of SUs, in the meantime, the total communication throughput is increased.