Title: Distributed spectrum-sharing in cognitive ad hoc networks using evolutionary game theory

Authors: Yifei Wei; Bo Gu; Yali Wang; Mei Song; Xiaojun Wang

Addresses: Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China ' Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China ' Products and Solutions-Network Research Department, Huawei Technologies Co., Ltd., Dongguan, 523808, China ' Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China ' School of Electronic Engineering, The Entwine Research Centre, Dublin City University, Dublin 9, Ireland

Abstract: As smart portable devices becoming increasingly popular and autonomous, the critical problem of spectrum congestion and inefficiency have drawn people's attention. Cognitive radio ad hoc networks (CRAHNs) is a promising solution to solve this problem. Due to its decentralised architecture, unstable network topology, highly fluctuated available spectrum, CRAHNs impose unique difficulties for spectrum sharing among CR users. A challenging question is how CR users could share vacant spectrum reasonably without centralised control. Hence, we formulate the vacant spectrum sharing among CR users in CRAHNs with evolutionary game theory (EGT). In the proposed game, we define the payoff of each CR user as a function of the achieved transmit rate and the interference to primary users. And we use replicator dynamics to model the strategy adaptation process. Simulation results suggest that the evolutionary equilibrium can be obtained through strategy adaptation and convergence is sensitive to the information latency.

Keywords: spectrum-sharing; cognitive networks; EGT; evolutionary game theory.

DOI: 10.1504/IJSNET.2019.100221

International Journal of Sensor Networks, 2019 Vol.30 No.3, pp.184 - 192

Available online: 18 Jun 2019 *

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