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Review Article · Open access · Published 21 May 2020

Deployment of Auction Theoretic Models for Spectrum Allocation in Cognitive Radio Networks

Monisha Devi1, Nityananda Sarma1 & Sanjib Kr. Deka1

Journal of Computer Science, Volume 16, Issue 5, pp. 632–641 · doi.org/10.3844/jcssp.2020.632.641

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Abstract

Cognitive Radio (CR) is a novel technology which empowers the unlicensed users to opportunistically avail the free channels left unoccupied by the licensed owners. This apparently resolves the spectrum scarcity problem arising in today’s telecommunication industry. In this technology, once the free bands (called spectrum holes) are detected using sensing techniques, next there is a need to efficiently redistribute the idle spectrum. Such an allocation process of CR has attracted several researchers across the world to contribute in this domain. With an initiative to analyze the functionality of spectrum allocation, this paper carries out a survey on the allocation mechanisms which have been applied to use the spectrum holes. We primarily focus our exploration on auction theoretic allocation models due to their efficacy in channel allocation. Auction formulation takes the unlicensed users as bidders where they bid for the spectrum holes as the auctioned item. Winner determination strategy and pricing strategy are two important aspects of an auction model which determines a fair allocation pattern and along with decides the monetary benefit of sellers and auctioneer. We go through a detailed study on single-sided auction and double-sided auction which are deployed with different CR network constraints to design the allocation model. Finally, we conclude the paper by underlining some future research directions in this area.

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Devi, M., Sarma, N. & Deka, S. K. (2020). Deployment of Auction Theoretic Models for Spectrum Allocation in Cognitive Radio Networks. Journal of Computer Science, 16(5), 632–641. https://doi.org/10.3844/jcssp.2020.632.641

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Deployment of Auction Theoretic Models for Spectrum Allocation in Cognitive Radio NetworksJournal of Computer Science · Volume 16, Issue 5 · pp. 632–641 · CC BY 3.0Download