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Energy detection investigation over composite α-μ/inverse-gamma wireless channel
- Source :
- AEU - International Journal of Electronics and Communications. 130:153556
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Proper utilization of the unused spectrum hole facilitates the expanding necessity of the elevated data rate in the upcoming 5th Generation (5G) wireless communication technology. Energy detection is a widely worked technique to fulfill this requirement with minimal time, cost, and efforts. With this motivation, this work develops an analytical framework to analyze the functioning of an energy detector (ED) based cognitive radio (CR) system over a composite fading distribution, characterized by α - μ /Inverse-Gamma (I-Gamma) composite fading channel. To begin with, closed-form expressions for the probability density function (PDF) are developed for single-input single-output (SISO) and single-input multiple-output (SIMO) channels. Exploiting these expressions, analytical results for the average probability of detection (PD) and the average area under the receiver operating characteristic curve (AUC) are obtained. Further, the breakdown is extended in determining average PD under high and very low signal-to-noise ratio (SNR) regime. Finally, the results are utilized as an application in analyzing the cooperative spectrum sensing (CSS) under different shadowing conditions. The optimization of the number of cognitive radios is carried out using the r-out-of-N voting rule. The validation of all the proposed results and their accuracy is determined using the Monte-Carlo simulations.
- Subjects :
- business.industry
Computer science
Detector
020206 networking & telecommunications
Probability density function
02 engineering and technology
Topology
03 medical and health sciences
0302 clinical medicine
Fading distribution
Cognitive radio
0202 electrical engineering, electronic engineering, information engineering
Wireless
Fading
Electrical and Electronic Engineering
business
030217 neurology & neurosurgery
Energy (signal processing)
Computer Science::Information Theory
Communication channel
Subjects
Details
- ISSN :
- 14348411
- Volume :
- 130
- Database :
- OpenAIRE
- Journal :
- AEU - International Journal of Electronics and Communications
- Accession number :
- edsair.doi...........12cff480835bf8a4aa56beda0c1fb77b
- Full Text :
- https://doi.org/10.1016/j.aeue.2020.153556