Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks

Xianfu Chen, Tao Chen, W. Cheng, H. Zhang

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

This paper addresses opportunistic spectrum access (OSA) in non-cooperative cognitive radio networks (CRNs). The selfish behaviors of the secondary users (SUs) will cause a CRN to collapse. The SUs are thus enabled to build beliefs about how other SUs would respond to their decision makings. The interaction among the SUs is modeled as a stochastic learning process. In this way, each SU can independently learn the behaviors of the competitors, optimize the OSA strategies, and finally achieve the goal of reciprocity. Two learning algorithms are proposed to stabilize the stochastic CRNs, the convergence properties of which are also proven theoretically. Simulation results validate the performance of the proposed results, and show that the achieved system performance outperforms some existing protocols.
Original languageEnglish
Title of host publicationProceedings
Subtitle of host publication8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages202-207
ISBN (Electronic)978-1-4799-2120-1
DOIs
Publication statusPublished - 2013
MoE publication typeA4 Article in a conference publication
Event8th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2013 - Washington, United States
Duration: 8 Jul 201310 Jul 2013
Conference number: 8

Conference

Conference8th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2013
Abbreviated titleCROWNCOM 2013
CountryUnited States
CityWashington
Period8/07/1310/07/13

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Cognitive radio
Learning algorithms
Decision making

Cite this

Chen, X., Chen, T., Cheng, W., & Zhang, H. (2013). Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks. In Proceedings: 8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013 (pp. 202-207). IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/CROWNCom.2013.6636818
Chen, Xianfu ; Chen, Tao ; Cheng, W. ; Zhang, H. / Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks. Proceedings: 8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013 . IEEE Institute of Electrical and Electronic Engineers , 2013. pp. 202-207
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title = "Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks",
abstract = "This paper addresses opportunistic spectrum access (OSA) in non-cooperative cognitive radio networks (CRNs). The selfish behaviors of the secondary users (SUs) will cause a CRN to collapse. The SUs are thus enabled to build beliefs about how other SUs would respond to their decision makings. The interaction among the SUs is modeled as a stochastic learning process. In this way, each SU can independently learn the behaviors of the competitors, optimize the OSA strategies, and finally achieve the goal of reciprocity. Two learning algorithms are proposed to stabilize the stochastic CRNs, the convergence properties of which are also proven theoretically. Simulation results validate the performance of the proposed results, and show that the achieved system performance outperforms some existing protocols.",
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Chen, X, Chen, T, Cheng, W & Zhang, H 2013, Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks. in Proceedings: 8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013 . IEEE Institute of Electrical and Electronic Engineers , pp. 202-207, 8th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2013, Washington, United States, 8/07/13. https://doi.org/10.1109/CROWNCom.2013.6636818

Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks. / Chen, Xianfu; Chen, Tao; Cheng, W.; Zhang, H.

Proceedings: 8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013 . IEEE Institute of Electrical and Electronic Engineers , 2013. p. 202-207.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AU - Chen, Tao

AU - Cheng, W.

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N2 - This paper addresses opportunistic spectrum access (OSA) in non-cooperative cognitive radio networks (CRNs). The selfish behaviors of the secondary users (SUs) will cause a CRN to collapse. The SUs are thus enabled to build beliefs about how other SUs would respond to their decision makings. The interaction among the SUs is modeled as a stochastic learning process. In this way, each SU can independently learn the behaviors of the competitors, optimize the OSA strategies, and finally achieve the goal of reciprocity. Two learning algorithms are proposed to stabilize the stochastic CRNs, the convergence properties of which are also proven theoretically. Simulation results validate the performance of the proposed results, and show that the achieved system performance outperforms some existing protocols.

AB - This paper addresses opportunistic spectrum access (OSA) in non-cooperative cognitive radio networks (CRNs). The selfish behaviors of the secondary users (SUs) will cause a CRN to collapse. The SUs are thus enabled to build beliefs about how other SUs would respond to their decision makings. The interaction among the SUs is modeled as a stochastic learning process. In this way, each SU can independently learn the behaviors of the competitors, optimize the OSA strategies, and finally achieve the goal of reciprocity. Two learning algorithms are proposed to stabilize the stochastic CRNs, the convergence properties of which are also proven theoretically. Simulation results validate the performance of the proposed results, and show that the achieved system performance outperforms some existing protocols.

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Chen X, Chen T, Cheng W, Zhang H. Reciprocity inspired learning for opportunistic spectrum access in cognitive radio networks. In Proceedings: 8th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2013 . IEEE Institute of Electrical and Electronic Engineers . 2013. p. 202-207 https://doi.org/10.1109/CROWNCom.2013.6636818