Analysis of Bayesian game theoretic approach for the target channel selection of secondary user under heterogeneous cognitive radio network

• Published in: Telecommunication systems 2024-05, Vol.86 (1), p.173-188
• Main Authors: Kundu, Arnab, Arif, Wasim
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Bayesian analysis; Business and Management; Cognitive radio; Computer Communication Networks; Game theory; IT in Business; Parameters; Players; Probability Theory and Stochastic Processes; Profits; Radio networks; Radio spectra; Spectrum allocation; Telecommunications systems; Uncertainty
• ISSN: 1018-4864; 1572-9451
• DOI: 10.1007/s11235-024-01118-5

This article delves into the investigation of parameters and associated issues in the context of a Bayesian game theory-based approach for selecting the target channel for secondary users in a licensed heterogeneous cognitive radio network. In such networks, cognitive or secondary users can enhance their activity within a licensed spectrum by dynamically selecting an available spectrum, thereby addressing the scarcity issue in the radio spectrum. The study adopts a game model where each user is treated as a network player, with the channel payoff or utility function serving as a crucial parameter for target channel selection. The game theory approach assumes that each player possesses knowledge of other players’ payoffs, although this assumption may only hold for some games. In auction-based games, for instance, other players’ payoffs or profits are unknown, introducing uncertainty. This type of game model falls under the Bayesian game model. The article presents the Bayesian battle of the sexes approach to address uncertainty in other players’ payoffs or profits and proposes possible causes for channel selection. The best response for secondary users and channel payoffs is computed using this approach. The Bayesian Nash equilibrium calculates the average payoff, taking into account various spectrum handoff parameters like waiting time and inactive probability. This comprehensive analysis aims to calculate the overall network characteristics in the given heterogeneous cognitive radio environment.