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Journal ArticleDOI

Performance Evaluation of PLC Under the Combined Effect of Background and Impulsive Noises

TLDR
The analysis presented in this letter closely predicts the behavior of the PLC system under the combined effect of background and impulsive noises.
Abstract
Power line communication (PLC) is the use of power lines for the purpose of electronic data transmission. The presence of additive noise, namely, background noise and impulsive noise, significantly affects the performance of a PLC system. While the background noise is modeled by Nakagami- $m$ distribution, the impulsive noise is modeled using Middleton class A distribution. In this letter, we study the performance of a PLC system under the combined effect of Nakagami- $m$ background noise and Middleton class A impulsive noise assuming binary phase shift keying signaling. The probability density function of decision variable under the influence of additive noise (sum of background noise and impulsive noise) is derived. We also derive an analytical expression for the average bit error rate of the considered PLC system. The analytical expressions are validated by close matching to the simulation results. The analysis presented in this letter closely predicts the behavior of the PLC system under the combined effect of background and impulsive noises.

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Citations
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Journal ArticleDOI

PLC performance evaluation with channel gain and additive noise over nonuniform background noise phase

TL;DR: The performance of a PLC system under the influence of Rayleigh distributed channel gain, background noise (with nonuniform phase), and impulsive noise is comprehensively studied and closed‐form expressions of the average bit error rate and outage probability for different cases depending on the presence or absence of impulsive Noise and channel gain are evaluated.
Proceedings ArticleDOI

Outage Probability Analysis of PLC with Channel Gain under Nakagami-m Additive Noise

TL;DR: This paper provides the performance analysis of a PLC system over Rician fading channel under Nakagami-m distributed additive background noise assuming binary phase shift keying modulation scheme and derives the probability density function of the decision variable and the instantaneous signal-to- noise ratio (SNR).
Journal ArticleDOI

Bit error probability of the M-QAM scheme under η-μ fading and impulsive noise in a communication system using spatial diversity

TL;DR: A new and exact expression for the bit error probability (BEP) of the square M‐ary quadrature amplitude modulation (M‐QAM) scheme is presented, with the channel under double gated additive white Gaussian noise and η‐μ fading in a communication system using the spatial diversity technique.
Journal ArticleDOI

Spatial Multiplexing-Based Minimum Distance Detection in Additive Generalized Gaussian Noise

TL;DR: A closed-form expression is derived for the pairwise error probability (PEP) in spatial multiplexing multiple-input multiple-output (MIMO) systems assuming that a minimum distance detector is employed.
Journal ArticleDOI

Low-density parity check coded orthogonal frequency division multiplexing for PLC in non-Gaussian noise using LLRs derived from effective noise probability density functions

TL;DR: In this paper, the performance of irregular low-density parity check (LDPC) coded orthogonal frequency division multiplexing (COFDM) utilising 4096 quadrature amplitude modulation (4096-QAM) is investigated over multipath power-line communication (PLC) channel.
References
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Book

Table of Integrals, Series, and Products

TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
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Probability, random variables and stochastic processes

TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
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Probability, random variables, and stochastic processes

TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
Journal ArticleDOI

Handbook of Mathematical Functions with Formulas

D. B. Owen
- 01 Feb 1965 - 
TL;DR: The Handbook of Mathematical Functions with Formulas (HOFF-formulas) as mentioned in this paper is the most widely used handbook for mathematical functions with formulas, which includes the following:
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