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Conference Papers Year : 2016

SOSAP: A Pareto-efficient Spectrum Access Protocol for Cognitive Radio Networks

Abstract

Decentralized cognitive radio networks (CRN) require efficient channel access protocols to enable cognitive secondary users (SUs) to access the primary channels in an opportunistic way without any coordination. In this paper, we develop a distributed spectrum access protocol for the case where the SUs aim to maximize the total system throughput while competing for spectrum resources. To model the competition amongst SUs, we formulate the spectrum access problem as a distributed welfare game, in which at each iteration each SU has to compute its marginal contribution to the system's welfare. Moreover, the SUs also need to decide which resource (channel) they should access at the next iteration. To address these challenges, we propose a stochastic learning algorithm based on payoff-based log-linear learning and prove its convergence towards a Pareto-efficient Nash equilibrium state.
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Dates and versions

hal-02292451 , version 1 (19-09-2019)

Identifiers

  • HAL Id : hal-02292451 , version 1

Cite

Stefano Iellamo, Marceau Coupechoux, Zaheer Khan. SOSAP: A Pareto-efficient Spectrum Access Protocol for Cognitive Radio Networks. IEEE Vehicular Technology Conference (VTC-Fall), Sep 2016, Montréal, Canada. pp.1-5. ⟨hal-02292451⟩
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