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Spectrum Sharing Optimization and Analysis in Cellular Networks under Target Performance and Budget Restriction

ASADUZZAMAN, Md, ABOZARIBA, Raouf and PATWARY, Mohammad (2017) Spectrum Sharing Optimization and Analysis in Cellular Networks under Target Performance and Budget Restriction. In: IEEE 85th Vehicular Technology Conference (VTC2017-Spring), 4th June – 7th June 2017, Sydney, Australia.

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Abstract or description

Dynamic Spectrum Sharing (DSS) aims to provide opportunistic access to under-utilised spectrum in cellular networks for secondary network operators. In this paper we propose an algorithm using stochastic and optimisation models to borrow spectrum bandwidths under the assumption that more resources exist for secondary access than the secondary network demand by considering a merchant mode. The main aim of the paper is to address the problem of spectrum borrowing in DSS environments, where a secondary network operator aims to borrow the required spectrum from multiple primary network operators to achieve a maximum profit under specific grade of service (GoS) and budget restriction. We assume that the primary network operators offer spectrum access opportunities with variable number of channels (contiguous and/or non-contiguous) at variable prices. Results obtained are then compared with results derived from an algorithm in which spectrum borrowing are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimisation framework is significantly higher than random counterpart.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Spectrum sharing, spectrum allocation, merchant mode, spectrum pricing, mathematical programming, aggregated channel allocation algorithms
Faculty: School of Creative Arts and Engineering > Art and Design
Event Title: IEEE 85th Vehicular Technology Conference (VTC2017-Spring)
Event Location: Sydney, Australia
Event Dates: 4th June – 7th June 2017
Depositing User: Md ASADUZZAMAN
Date Deposited: 10 Feb 2017 12:39
Last Modified: 24 Feb 2023 13:46
URI: https://eprints.staffs.ac.uk/id/eprint/2987

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