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research-article

Collaborative spectrum sensing mechanism based on user incentive in cognitive radio networks

Authors:

Masahiro Sasabe,

Tomohiro Nishida,

Shoji KasaharaAuthors Info & Claims

Volume 147, Issue C

Pages 1 - 13

https://doi.org/10.1016/j.comcom.2019.08.012

Published: 01 November 2019 Publication History

Abstract

In cognitive radio networks (CRNs), it is important for secondary users (SUs) to efficiently reuse spectrum without interfering communication of primary users (PUs). To acquire the communication opportunities, SUs first need become winning, i.e., suppressing its own miss detection probability under the upper limit imposed by PUs. Collaborative spectrum sensing (CSS) is a promising approach to improve the detection performance of SUs, where multiple SUs form a group and share their sensing results. In addition, the probability that winning SUs correctly detect idle state of PUs’ spectrum will affect their communication opportunities. We first formulate a global optimization problem as integer linear programming (ILP), which maximizes both the number of winning SUs and total communication opportunities among them. In CSS, we also have to consider the selfishness of SUs because winning SUs will compete with group members to acquire their own communication opportunities. To cope with this competitive problem in addition to scalability problem of the global optimization, we further formulate an individual optimization problem, which can be solved by a user-incentive based CSS mechanism composed of PU selection and group (re)formation among SUs, where communication opportunities are allocated to SUs according to their detection performance. Through simulation experiments, we show the proposed mechanism considering selfishness of SUs is competitive with the existing scheme based on group-level cooperation, in terms of both the ratio of winning SUs and total communication opportunities among them. Comparing with the global optimization, we also show that the proposed mechanism can support larger-scale systems with performance improvement. In addition, we show that the proposed mechanism can achieve stable group formation even under SUs’ selfish behavior. Finally, we discuss how the number of PUs affects the system performance.

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Cited By

Rangaraj NJothiraj SBalu S(2022)Hybrid Optimized Secure Cooperative Spectrum Sensing for Cognitive Radio NetworksWireless Personal Communications: An International Journal10.1007/s11277-021-09402-2124:2(1209-1227)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1007/s11277-021-09402-2
Bagheri AEbrahimzadeh ANajimi M(2020)Game-theory-based lifetime maximization of multi-channel cooperative spectrum sensing in wireless sensor networksWireless Networks10.1007/s11276-020-02369-126:6(4705-4721)Online publication date: 22-May-2020
https://dl.acm.org/doi/10.1007/s11276-020-02369-1

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Collaborative spectrum sensing mechanism based on user incentive in cognitive radio networks

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Information & Contributors

Information

Published In

cover image Computer Communications

Computer Communications Volume 147, Issue C

Nov 2019

252 pages

ISSN:0140-3664

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Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 November 2019

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Cited By

Rangaraj NJothiraj SBalu S(2022)Hybrid Optimized Secure Cooperative Spectrum Sensing for Cognitive Radio NetworksWireless Personal Communications: An International Journal10.1007/s11277-021-09402-2124:2(1209-1227)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1007/s11277-021-09402-2
Bagheri AEbrahimzadeh ANajimi M(2020)Game-theory-based lifetime maximization of multi-channel cooperative spectrum sensing in wireless sensor networksWireless Networks10.1007/s11276-020-02369-126:6(4705-4721)Online publication date: 22-May-2020
https://dl.acm.org/doi/10.1007/s11276-020-02369-1

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