Paper-VT-2013-00732.R1.pdf (296.41 kB)
Distributed learning-based spectrum allocation with noisy observations in cognitive radio networks
journal contribution
posted on 2016-11-10, 10:21 authored by Mahsa DerakhshaniMahsa Derakhshani, Tho Le-NgocThis paper studies the medium access design for secondary users (SUs) from a game-theoretic learning perspective. In consideration of the random return of primary users (PUs), a distributed SU access approach is presented based on an adaptive carrier sense multiple access (CSMA) scheme, in which each SU accesses multiple idle frequency slots of a licensed frequency band with adaptive activity factors. The problem of finding optimal activity factors of SUs is formulated as a potential game, and the existence, feasibility, and optimality of Nash equilibrium (NE) are analyzed. Furthermore, to achieve NEs of the formulated game, learning-based algorithms are developed in which each SU independently adjusts its activity factors. Convergence properties of best-response dynamics and log-linear dynamics are studied. Subsequently, by learning other SUs' behavior from locally available information, the convergence with probability of one to an arbitrarily small neighborhood of the globally optimal solution is investigated by both analysis and simulation.
Funding
The work presented in this paper is partly supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Program, and the NSERC Collaborative Research and Development Grant with BlackBerry
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
IEEE Transactions on Vehicular TechnologyVolume
63Issue
8Pages
3715 - 3725Citation
DERAKHSHANI, M. and LE-NGOC, T., 2014. Distributed learning-based spectrum allocation with noisy observations in cognitive radio networks. IEEE Transactions on Vehicular Technology, 63 (8), pp. 3715 - 3725.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2014-01-28Publication date
2014Notes
This article was published in the journal IEEE Transactions on Vehicular Technology [© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works] . The definitive version is available at: http://dx.doi.org/10.1109/TVT.2014.2309120ISSN
0018-9545Publisher version
Language
- en