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Single-sided truthful auction mechanism for heterogeneous channel allocation in cognitive radio networks

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Abstract

In order to alleviate imbalances in radio spectrum usage, cognitive radio (CR) is designed as a dominant solution, which constantly senses the spectrum for free bands and opportunistically utilizes those bands to improve spectrum utilization. One of the essential functionalities of this emerging technology is to efficiently allocate licensed unused channels amongst Secondary Users (SUs). With this initiative, this paper deploys an auction theoretical model to provide transparent resource allocation. Auction offers a market-based mechanism where an auctioneer (primary owner) fairly leases its free channels to desirable buyers (SUs). In this paper, we propose a single-sided sealed-bid multi-unit auction mechanism for CR networks (CRNs) which sells temporarily available heterogeneous channels amongst SUs at suitable rates. Differences in channel availability time and dynamics in spectrum opportunities decide bid collection from SUs while reducing the possibility of disruption during SUs’ transmission using the allocated channels. Multiple auction rounds with concurrent bidding allows the mechanism to make utmost use of the scarce radio resource. The proposed model derives a winner determination algorithm and a payment rule to select the winning bidders and their respective expenses. Additionally, we provide the proofs of truthfulness and individual rationality to obtain an economically robust auction. Simulation based results indicate performance improvements in the proposed model in terms of spectrum utilization, auctioneer’s revenue, utility per buyer, user satisfaction compared to a similar approach from literature.

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  1. Department of Computer Science and Engineering, Tezpur University, Tezpur, 784028, India

    Monisha Devi, Nityananda Sarma & Sanjib Deka

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  1. Monisha Devi
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  2. Nityananda Sarma
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Correspondence to Monisha Devi.

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Devi, M., Sarma, N. & Deka, S. Single-sided truthful auction mechanism for heterogeneous channel allocation in cognitive radio networks. Wireless Netw 29, 3445–3467 (2023). https://doi.org/10.1007/s11276-023-03412-7

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