SEP analysis on the κ-μ shadowed fading with additive Laplacian noise

IF 2.9 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Puspraj Singh Chauhan , Paresh Chandra Sau , Sandeep Kumar , Ankit Jain , Vimal Bhatia
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引用次数: 0

Abstract

Through this correspondence, we present a theoretical framework for assessing the functionality of communication systems when operating over the family of κ-μ shadowed fading impacted by additive Laplacian noise. In this context, we have addressed the κ-μ shadowed Type-I, κ-μ shadowed Type-II and κ-μ shadowed Type-III fading channels and analyzed the impact of various shadowing types on the performance metrics of the communication systems. This study also examines the error probability for binary phase shift keying, quadrature phase shift keying, and M-ary phase shift keying. We have also derived generalized solutions to the moment-generating functions. In addition, we conducted an analysis of the shadowing impact using the probability density function and error probability. Furthermore, low complex approximate expressions for the error probability are presented. We additionally corroborate the theoretical results with numerical and Monte-Carlo simulations.
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来源期刊
Digital Signal Processing
Digital Signal Processing 工程技术-工程:电子与电气
CiteScore
5.30
自引率
17.20%
发文量
435
审稿时长
66 days
期刊介绍: Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,
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