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Journal ArticleDOI

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

TL;DR: 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.
Citations
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Proceedings ArticleDOI
21 May 2017
TL;DR: An improvement to the end-to-end bit error rate (E2E-BER) performance of turbo-coded orthogonal frequency division multiplexing for physical layer network coding (TC-OFDM-PLNC) over power line communication (PLC) channels in the presence of impulsive noise is presented.
Abstract: This paper presents an improvement to the end-to-end bit error rate (E2E-BER) performance of turbo-coded orthogonal frequency division multiplexing for physical layer network coding (TC-OFDM-PLNC) over power line communication (PLC) channels in the presence of impulsive noise. A novel detection scheme is introduced to transform the transmit signal constellation based on the frequency-domain channel coefficients in order to improve the performance of the turbo decoder at the relay node and end nodes, respectively, on a link-by-link (LBL) basis utilizing newly derived noise probability density functions (PDFs). Moreover, the closed-form expressions of the BER at the relay, end nodes and E2E are derived, in addition to the E2E average BER upper-bound (AUB). Monte Carlo simulation results closely verify the validity of the derived analytical expressions and reveal that the proposed method utilizing exact derived PDFs for impulsive probability α = 10−1 gives coding gains of 4.5 dB and 8.5 dB at P e = 10−4 for the minimum mean square error (MMSE) and the zero forcing (ZF) equalizers, respectively, compared to the conventional TC-OFDM-PLNC system.

4 citations


Cites background from "Performance Evaluation of PLC Under..."

  • ...However, in many studies, frequency selectivity due to multipath propagation in PLC channels has been ignored in the receiver derivations resulting in BER degradation of TC-OFDM-PLNC systems [10], [11]....

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Journal ArticleDOI
TL;DR: A joint detection and estimation algorithm based on Bayesian statistical inference is devised to accomplish the CD task, which can not only accurately detect the unknown channel status, but also estimate the real-time channel state information (CSI), thereby eliminating their effects on the detection performance.
Abstract: The advanced 6G Technology benefits the Internet of Things (IoT) in various applications. As one essential application scenario, smart grid (SG) incorporates communication and management techniques and promises an efficient and intelligent power system, whereby cognitive radio (CR) is believed to be an essential tool for better resource utilization in power generation and delivering processes. In the CR-assisted IoT in SG scenarios, channel detection (CD) will play an essential role to accurately sense the available channel resource. However, for SG scenarios, high-accuracy CD may become a challenging task in complex power supply environments with unexpected impulsive noise (IN) and channel fading, which will significantly affect the signal statistical property. To address this problem, we propose a novel CD mechanism in the context of the wireless environment with IN and random channel fading. To be specific, taking the wireless channel status, IN and time-variant fading into account, a novel quaternary hypothesis testing model (QHTM) is formulated to describe the detection task, and by which a new dynamic state-space model (DSM) is developed to capture the dynamical behavior of the CD system. On this basis, a joint detection and estimation algorithm based on Bayesian statistical inference is devised to accomplish the CD task. Benefiting from the joint posteriori distribution estimation procedure, our algorithm can not only accurately detect the unknown channel status, but also estimate the real-time channel state information (CSI), thereby eliminating their effects on the detection performance. Numerical simulation results validate the proposed CD mechanism.

4 citations

Proceedings ArticleDOI
15 Apr 2020
TL;DR: The research demonstrated that the proposed algorithms trained on the PLC signals features achieved high classification accuracy, for instance the PNN obtained classification accuracy of 94.3% whilst the classification accuracy produced by the SVM using fine Gaussian kernel function was 96.4%.
Abstract: For the past many years, Artificial Neural Networks (ANNs) have shown powerful performance in many applications. In this paper, the usage of ANNs in pattern recognition (discriminant analysis) have been studied and examined. For the purpose of detecting noise that presents in OFDM signals after being transmitted over a PLC channel, two classification learners were proposed. These classifiers are multiclass support vector machines (SVMs) with the error-correcting output codes (ECOC) and probabilistic neural networks (PNNs). A training dataset of 5,000 randomly generated signals transmitted over PLC channels, where each received signal is associated with its category based on its amplitude, was used to train the proposed classifiers. The purpose of this study was to decide on the optimum classification scheme among the proposed methods in terms of computational cost and classification accuracy. In general, our research demonstrated that our proposed algorithms trained on the PLC signals features achieved high classification accuracy, for instance the PNN obtained classification accuracy of 94.3% whilst the classification accuracy produced by the SVM using fine Gaussian kernel function was 96.4%. Therefore, they can be viewed as robust supervised classification learners.

4 citations


Additional excerpts

  • ...foundation present everywhere [4-6]....

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Book ChapterDOI
23 Oct 2017
TL;DR: It is found that under some network setup, there exists a threshold power for which the actual gameplay of the legitimate nodes does not depend upon the actions of the jamming node, and vice versa, which allows us to choose the appropriate power allocation schemes given the total power and the action of thejamming node in some cases.
Abstract: In this paper, we investigate the performance of power line communication (PLC) network in the presence of jamming attacks. The legitimate nodes of the PLC network try to communicate with the anchor node of the network while the jamming node attempts to degrade the system performance. The fading, attenuation and colored noise of the PLC channel with dependence on the frequency and transmission distance are taken into account. To investigate the jamming problem, we frame the adversarial interaction into a Bayesian game, where the PLC network tries to maximize the overall expected network capacity and the jammer node has the opposite goal. In the Bayesian game, both players have imperfect knowledge of their opponents. We study effects of total power available to the players on the equilibrium of the game by formulating it into zero-sum and non-zero-sum games, respectively. It is found that under some network setup, there exists a threshold power for which the actual gameplay of the legitimate nodes does not depend upon the actions of the jamming node, and vice versa. This allows us to choose the appropriate power allocation schemes given the total power and the action of the jamming node in some cases.

4 citations

References
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Book
01 Jan 1943
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
Abstract: 0 Introduction 1 Elementary Functions 2 Indefinite Integrals of Elementary Functions 3 Definite Integrals of Elementary Functions 4.Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integrals of Special Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequalities 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform

27,354 citations

Book
01 Jan 1965
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.
Abstract: Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing Theory

13,886 citations

Book
01 Jan 2002
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.
Abstract: Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing Theory

12,407 citations

Journal ArticleDOI
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:
Abstract: (1965). Handbook of Mathematical Functions with Formulas. Technometrics: Vol. 7, No. 1, pp. 78-79.

7,538 citations