Radio resource sharing framework for cooperative multioperator networks with dynamic overflow modeling

Abozariba, Raouf and Asaduzzaman, Md and Patwary, Mohammad N. (2017) Radio resource sharing framework for cooperative multioperator networks with dynamic overflow modeling. IEEE Transactions on Vehicular Technology, 66 (3). pp. 2433-2447. ISSN 0018-9545

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Abstract

Due to exponentially growing wireless applications and services, traffic demand is rapidly increasing. To cope with such growth, wireless network operators seek radio resource cooperation strategies for their users with the highest grade of service possible. In this paper, we propose a set of analytical models for dynamic spectrum access (DSA) to attain intranetwork resource sharing agreements and adopt such strategies by sharing radio resources. The proposed models focus on reducing blocking probability for a secondary network to attain wireless services as a tradeoff with a marginal increase in the blocking probability of a primary network in return for monetary rewards. We derived the global balance equation and an explicit expression of the blocking probability for each resource sharing model. The robustness of the proposed analytical models is evaluated under different scenarios by considering varying traffic intensities and different network sizes and adding reserved resources. The results show that the blocking probabilities can be significantly reduced with the proposed DSA framework in comparison to the existing local spectrum access schemes.

Item Type: Journal Article
Journal or Publication Title: IEEE Transactions on Vehicular Technology
Additional Information: ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2200/2202
Subjects:
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 128868
Deposited By: ep_importer_pure
Deposited On: 09 Nov 2018 11:00
Refereed?: Yes
Published?: Published
Last Modified: 20 Feb 2020 03:57
URI: https://eprints.lancs.ac.uk/id/eprint/128868

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