Sofotasios, PC, Rebeiz, E, Zhang, L et al. (3 more authors) (2013) Energy Detection Based Spectrum Sensing Over k-μ and k-μ Extreme Fading Channels. IEEE Transactions on Vehicular Technology, 62 (3). pp. 1031-1040. ISSN 0018-9545
Abstract
Energy detection (ED) is a simple and popular method of spectrum sensing in cognitive radio systems. It is also widely known that the performance of sensing techniques is largely affected when users experience fading effects. This paper investigates the performance of an energy detector over generalized κ-μ and κ- μ extreme fading channels, which have been shown to provide remarkably accurate fading characterization. Novel analytic expressions are firstly derived for the corresponding average probability of detection for the case of single-user detection. These results are subsequently extended to the case of square-law selection (SLS) diversity and for collaborative detection scenarios. As expected, the performance of the detector is highly dependent upon the severity of fading since even small variations of the fading conditions affect significantly the value of the average probability of detection. Furthermore, the performance of the detector improves substantially as the number of branches or collaborating users increase in both severe and moderate fading conditions, whereas it is shown that the κ- μ extreme model is capable of accounting for fading variations even at low signal-to-noise values. The offered results are particularly useful in assessing the effect of fading in ED-based cognitive radio communication systems; therefore, they can be used in quantifying the associated tradeoffs between sensing performance and energy efficiency in cognitive radio networks.μ
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012 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. |
Keywords: | Collaborative spectrum sensing; diversity; energy detector; fading channels; κ−μ fading; spectrum sensing; unknown signal detection |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Apr 2019 14:01 |
Last Modified: | 09 Apr 2019 14:01 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TVT.2012.2228680 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109522 |