NDLI: Unified approach for probability of detection evaluation over generalised fading channels

Content Provider	IET Digital Library
Author	Ayadi, Moataz M. H. El Ismail, Mahmoud H. Alhennawi, Husam R.
Abstract	In this study, the authors revisit energy detection-based spectrum sensing cognitive radio systems operating over generalised fading channels. In particular, they derive closed-form exact expressions as well as low- and high-signal-to-noise ratio asymptotic expansions for the misdetection probability over the Fox's H-function fading channel. The closed-form expression is given in terms of the bivariate Fox's H-function and subsumes most of the expressions previously presented in the literature. Also, the obtained asymptotic expressions are very easy to compute and can be used to get various performance insights. We verified, theoretically and numerically, the validity of the exact expression for important special cases previously reported in the literature, namely the Nakagami-m and the extended generalised-K fading distributions. Numerical results also demonstrate the high accuracy of the asymptotic expansions.
Starting Page	1532
Ending Page	1541
Page Count	10
ISSN	17518628
Volume Number	10
e-ISSN	17518636
Issue Number	Issue 12, Aug (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/10/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2016.0108
Journal	IET Communications
Publisher Date	2016-08-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Asymptotic Expression Cognitive Radio Detection Evaluation Probability Energy Detection-based Spectrum Sensing Cognitive Radio System Fox H-function Fading Channel Generalised Fading Channel Generalised-K Fading Distribution High-signal-to-noise Ratio Asymptotic Expansion Legislation, Frequency Allocation And Spectrum Pollution Low-signal-to-noise Ratio Asymptotic Expansion Misdetection Probability Nakagami Channel Nakagami-m Fading Distribution Probability Radio Link And Equipment Radio Spectrum Management Signal Detection Statistics
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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