Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81706
Title: Distributed boundary estimation for spectrum sensing in cognitive radio networks
Authors: Zhang, Yi
Tay, Wee Peng
Li, Kwok Hung
Gaïti, Dominique
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
Issue Date: 2014
Source: Zhang, Y., Tay, W. P., Li, K. H., & Gaïti, D. (2014). Distributed boundary estimation for spectrum sensing in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 32(11), 1961-1973.
Series/Report no.: IEEE Journal on Selected Areas in Communications
Abstract: In a cognitive radio network, a primary user (PU) shares its spectrum with secondary users (SUs) temporally and spatially, while allowing for some interference. We consider the problem of estimating the no-talk region of the PU, i.e., the region outside which SUs may utilize the PU's spectrum regardless of whether the PU is transmitting or not. We propose a distributed boundary estimation algorithm that allows SUs to estimate the boundary of the no-talk region collaboratively through message passing between SUs, and analyze the trade-offs between estimation error, communication cost, setup complexity, throughput and robustness. Simulations suggest that our proposed scheme has better estimation performance and communication cost trade-off compared to several other alternative benchmark methods, and is more robust to SU sensing errors, except when compared to the least squares support vector machine approach, which however incurs a much higher communication cost.
URI: https://hdl.handle.net/10356/81706
http://hdl.handle.net/10220/25255
DOI: 10.1109/JSAC.2014.1411RP08
Rights: © 2014 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 published version is available at: [http://dx.doi.org/10.1109/JSAC.2014.1411RP08].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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