Fifty Years of Noise Modeling and Mitigation in Power-Line Communications.

Building on the ubiquity of electric power infrastructure, power line communications (PLC) has been successfully used in diverse application scenarios, including the smart grid and in-home broadband communications systems as well as industrial and home automation. However, the power line channel exhibits deleterious properties, one of which is its hostile noise environment. This article aims for providing a review of noise modeling and mitigation techniques in PLC. Specifically, a comprehensive review of representative noise models developed over the past fifty years is presented, including both the empirical models based on measurement campaigns and simplified mathematical models. Following this, we provide an extensive survey of the suite of noise mitigation schemes, categorizing them into mitigation at the transmitter as well as parametric and non-parametric techniques employed at the receiver. Furthermore, since the accuracy of channel estimation in PLC is affected by noise, we review the literature of joint noise mitigation and channel estimation solutions. Finally, a number of directions are outlined for future research on both noise modeling and mitigation in PLC

Noise Characterization and Emulation for Low-Voltage Power Line Channels between 150 kHz and 10 MHz

Characterization and emulation of power line noise have attracted interest since long, in both narrowband and broadband applications. Based on existing models, this paper presents a systematic approach to extract and parameterize each subtype of low-voltage (LV) power line noise between 150 kHz and 10 MHz. Based on the characterization, a FPGA-based emulator is proposed to emulate power line noise scenarios flexibly. A LV power line noise measuring platform is also presented with sample measurements and their emulation

Multiscaling analysis and modelling of bursty impulsive noise in broadband power line communication channels.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2017.Power line communication (PLC) networks have the potential to offer broadband application services to homes and small offices cheaply since no additional wiring is required for it implementation. However, like other communication systems, it has its own challenges and the understanding of its channel characteristics is key to its optimal performance evaluation and deployment. Multipath propagation due to impedance mismatch and bursty impulsive noise are the important challenges that must be understood and their effects minimized for optimal system performance. Noise in power line communication networks is non-Gaussian and as such cannot be modelled as the convenient additive white Gaussian noise. The noise is known to be impulsive and in most cases, occurs in bursts. Therefore, it can be referred as bursty impulsive noise. Due to unique nature of this noise in power line channels, modulation and decoding schemes optimized for Gaussian channels may not necessarily work well in PLC systems. Recently developed noise models though take into consideration memory inherent in PLC noise, models capturing both long range correlations and multiscaling behaviour are not yet available in the literature. Furthermore, even though it is known that PLC noise has memory (i.e., it is correlated), the statistical properties of it is not well documented in the literature and will be the focus of this thesis. In this thesis, multiscaling behaviour of PLC noise is investigated. Both fractal and multifractal analysis methods are employed on noise data collected in three different scenarios (small offices, stand-alone apartment and University electronic laboratory) and their characteristics analysed. Multifractal analysis is employed since it is able to characterize both the strengths and frequency of occurrence of bursts in power line noise. Specifically, the contributions in this thesis are as follows: Firstly, empirical evidence is provided that PLC noise clearly manifests long range correlations behaviour. This is achieved by calculating the Hurst parameter (which is a measure of self similarity) in data from the above scenarios. Various methods employed to estimate this Hurst parameter reveal that in all the scenarios, long range dependence is evidenced. Secondly, multifractal detrended fluctuation analysis (MDFA) and multifractal detrending moving average (MDMA) analysis have been used to investigate the temporal correlations and scaling behaviour of power line channel noise measured from the three different scenarios mentioned earlier. Empirical results show that power line noise clearly manifests both long-range correlation and multifractal scaling behaviour with different strengths depending on the environments where they were captured. From the estimated singularity spectrum which is left truncated, it is evident from the two methods used that power line noise is sensitive to small fluctuations and is characterized by large scaling exponents. Multifractal analysis of the reshuffled time series noise reveal that the multifractal nature of PLC noise is as a result of long range correlation inherent in the noise and not from the heavy tailed distributions in it. Thirdly, we propose a multiplicative cascade model for PLC noise that is able to reproduce the empirical findings concerning the PLC noise time series: its local scaling behaviour and long range correlations. Model parameters are derived from the shape of multifractal spectrum of the PLC time series noise collected from measurement campaigns. Since in the recent past, the main challenge in PLC systems has been on how to model bursty impulsive PLC noise, the proposed model will be very useful in evaluating system performance of PLC networks in the presence of the bursty impulsive noise inherent in PLC networks. Moreover, bursts of different frequencies and strengths can be modelled by this proposed model and hence their effects on system performance evaluated. This will also open up investigations into designing modulation and decoding schemes that are optimal in systems prone to bursty impulsive noise

On noise modeling for power line communications

Abstract-This paper reviews existing noise models including both background and impulsive noise for the in-home PLC scenario, highlighting similarities and differences. With reference to the impulsive noise, it is shown that a simple model, in the frequency band up to 100 MHz, can be derived by considering the noise generated at the source and taking into account the effect of the channel. Capacity considerations are then made, comparing erasure decoding strategies or full decoding strategies

SOM-Based Approach for the Analysis and Classification of Synchronous Impulsive Noise of an In-Ship PLC System

The interest in wideband data transmission over power line communications has increased rapidly. This technology offers a convenient and inexpensive medium to transmit data, reducing the number of cables. This advantage is particularly appealing in many fields, like the railway, naval, and aeronautical ones. Nevertheless, several problems have to be faced to obtain a high data rate. In particular, the presence of noise makes the transmission difficult, degrading the quality of received signals and prohibiting the full application of these communication frameworks. In this paper the behaviour of an in-ship powerline communication system is analyzed in the presence of synchronous periodic impulsive noise. Such noise is modelled at source and its effects on the transmission of wideband signals are evaluated by means of a simulation circuit model. The obtained results allow to identify the characteristics of the channel and the critical conditions due to noise. Subsequently, an unsupervised technique based on principal component analysis and fuzzy c-mean classifier detects the presence and classifies the specific noises. Numerical results show that the proposed approach enables to achieve this target accurately under different operating conditions, proving to be an effective tool to enhance the performances of the considered technology

Contributions à l'étude des communications numériques sur le réseau électrique à l'intérieur des bâtiments : modélisation du canal et optimisation du débit

In recent years, the electrical network has become an essential candidate for high-speed data transmission inside buildings. Many solutions are currently underway in order to optimize these technologies known under the name of in-home Power-Line Communications (PLC). Multiple-Input Multiple-Output (MIMO) technique has recently been transposed into power-line networks for which different signal feeding possibilities can be considered between phase, neutral and earth wires. In this thesis, we propose two original contributions to indoor broadband PLC. The first contribution concerns the MIMO-PLC channel modeling. Based on a Single-Input Single-Output (SISO) parametric channel model presented in the literature, we propose a MIMO one by considering a new parameter which characterizes the spatial correlation. The proposed model enables an accurate description of the spatial correlation of European MIMO PLC field measurements. The second contribution is related to the impulsive noise present in power-line networks which constitutes a major problem in communications systems. We propose an outage capacity approach in order to optimize the average data rate in Orthogonal Frequency Division Multiplexing (OFDM) systems affected by impulsive noise. First, we study the channel capacity as a function of a noise margin provided to the transmitted symbols. Then we determine the analytical expression of the outage probability of an OFDM symbol in terms of the noise margin, by studying in detail the interaction between the noise impulse and the symbol. Based on the two aforementioned relations, we deduce the outage capacity. Then we propose an approach that enables to maximize the average system data rate. Finally, we present the results in the particular case of indoor broadband PLC in the presence of impulsive noise.Au cours de ces dernières années, le réseau électrique est devenu un candidat incontournable pour la transmission de données à haut débit à l’intérieur des bâtiments. De nombreuses solutions sont actuellement à l’étude afin d’optimiser ces technologies connues sous le nom Courants Porteurs en Ligne (CPL) ou PLC (Power-Line Communications). La technique MIMO (Multiple-Input Multiple-Output) a été tout récemment transposée au réseau filaire électrique pour lequel différents modes d’alimentation peuvent être envisagés entre la phase, le neutre et la terre. Dans le cadre de cette thèse, nous proposons deux contributions originales à l’étude des communications numériques sur le réseau électrique à l’intérieur des bâtiments. La première contribution concerne la modélisation du canal MIMO-PLC. En repartant d’un modèle du canal paramétrique SISO (Single-Input Single-Output) connu dans la littérature, nous proposons un modèle du canal MIMO en considérant un nouveau paramètre caractérisant la corrélation spatiale. Le modèle proposé permet de représenter fidèlement la corrélation spatiale des mesures effectuées à l’échelle européenne. La deuxième contribution concerne le bruit impulsif présent sur le réseau électrique domestique qui constitue un problème majeur dans les systèmes de communications. Nous proposons une méthode basée sur la notion de capacité de coupure afin d’optimiser le débit moyen dans les systèmes OFDM (Orthogonal Frequency Division Multiplexing) soumis aux bruits impulsifs. D’abord, nous étudions la capacité du système en fonction d’une marge de bruit fournie aux symboles transmis. Ensuite, nous déterminons l’expression analytique de la probabilité de coupure (outage) d’un symbole OFDM en fonction de cette marge, en étudiant de manière détaillée l’interaction entre l’impulsion de bruit et le symbole. A partir de ces deux calculs, nous déduisons la capacité de coupure. Puis, nous proposons une approche qui maximise l’espérance mathématique du débit reçu. Finalement, nous présentons les résultats obtenus dans le cas particulier d’une transmission à haut débit sur PLC en présence de bruits impulsifs

Classification and modeling of power line noise using machine learning techniques

A thesis submitted in ful lment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering Faculty of Engineering and Built Environment June 2017The realization of robust, reliable and e cient data transmission have been the theme of recent research, most importantly in real channel such as the noisy, fading prone power line communication (PLC) channel. The focus is to exploit old techniques or create new techniques capable of improving the transmission reliability and also increasing the transmission capacity of the real communication channels. Multi-carrier modulation scheme such as Orthogonal Frequency Division Multiplexing (OFDM) utilizing conventional single-carrier modulation is developed to facilitate a robust data transmission, increasing transmission capacity (e cient bandwidth usage) and further reducing design complexity in PLC systems. On the contrary, the reliability of data transmission is subjected to several inhibiting factors as a result of the varying nature of the PLC channel. These inhibiting factors include noise, perturbation and disturbances. Contrary to the Additive White Gaussian noise (AWGN) model often assumed in several communication systems, this noise model fails to capture the attributes of noise encountered on the PLC channel. This is because periodic noise or random noise pulses injected by power electronic appliances on the network is a deviation from the AWGN. The nature of the noise is categorized as non-white non-Gaussian and unstable due to its impulsive attributes, thus, it is labeled as Non-additive White Gaussian Noise (NAWGN). These noise and disturbances results into long burst errors that corrupts signals being transmitted, thus, the PLC is labeled as a horrible or burst error channel. The e cient and optimal performance of a conventional linear receiver in the white Gaussian noise environment can therefore be made to drastically degrade in this NAWGN environment. Therefore, transmission reliability in such environment can be greatly enhanced if we know and exploit the knowledge of the channel's statistical attributes, thus, the need for developing statistical channel model based on empirical data. In this thesis, attention is focused on developing a recon gurable software de ned un-coded single-carrier and multicarrier PLC transceiver as a tool for realizing an optimized channel model for the narrowband PLC (NB-PLC) channel. First, a novel recon gurable software de ned un-coded single-carrier and multi-carrier PLC transceiver is developed for real-time NB-PLC transmission. The transceivers can be adapted to implement di erent waveforms for several real-time scenarios and performance evaluation. Due to the varying noise parameters obtained from country to country as a result of the dependence of noise impairment on mains voltages, topology of power line, place and time, the developed transceivers is capable of facilitating constant measurement campaigns to capture these varying noise parameters before statistical and mathematically inclined channel models are derived. Furthermore, the single-carrier (Binary Phase Shift Keying (BPSK), Di erential BPSK (DBPSK), Quadrature Phase Shift Keying (QPSK) and Di erential QPSK (DQPSK)) PLC transceiver system developed is used to facilitate a First-Order semi-hidden Fritchman Markov modeling (SHFMM) of the NB-PLC channel utilizing the e cient iterative Baum- Welch algorithm (BWA) for parameter estimation. The performance of each modulation scheme is evaluated in a mildly and heavily disturbed scenarios for both residential and laboratory site considered. The First-Order estimated error statistics of the realized First- Order SHFMM have been analytically validated in terms of performance metrics such as: log-likelihood ratio (LLR), error-free run distribution (EFRD), error probabilities, mean square error (MSE) and Chi-square ( 2) test. The reliability of the model results is also con rmed by an excellent match between the empirically obtained error sequence and the SHFMM regenerated error sequence as shown by the error-free run distribution plot. This thesis also reports a novel development of a low cost, low complexity Frequency-shift keying (FSK) - On-o keying (OOK) in-house hybrid PLC and VLC system. The functionality of this hybrid PLC-VLC transceiver system was ascertained at both residential and laboratory site at three di erent times of the day: morning, afternoon and evening. A First and Second-Order SHFMM of the hybrid system is realized. The error statistics of the realized First and Second-Order SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2). The Second-Order SHFMMs have also been analytically validated to be superior to the First-Order SHFMMs although at the expense of added computational complexity. The reliability of both First and Second-Order SHFMM results is con rmed by an excellent match between the empirical error sequences and SHFMM re-generated error sequences as shown by the EFRD plot. In addition, the multi-carrier (QPSK-OFDM, Di erential QPSK (DQPSK)-OFDM) and Di erential 8-PSK (D8PSK)-OFDM) PLC transceiver system developed is used to facilitate a First and Second-Order modeling of the NB-PLC system using the SHFMM and BWA for parameter estimation. The performance of each OFDM modulation scheme in evaluated and compared taking into consideration the mildly and heavily disturbed noise scenarios for the two measurement sites considered. The estimated error statistics of the realized SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2) test. The estimated Second-Order SHFMMs have been analytically validated to be outperform the First-Order SHFMMs although with added computational complexity. The reliability of the models is con rmed by an excellent match between the empirical data and SHFMM generated data as shown by the EFRD plot. The statistical models obtained using Baum-Welch to adjust the parameters of the adopted SHFMM are often locally maximized. To solve this problem, a novel Metropolis-Hastings algorithm, a Bayesian inference approach based on Markov Chain Monte Carlo (MCMC) is developed to optimize the parameters of the adopted SHFMM. The algorithm is used to optimize the model results obtained from the single-carrier and multi-carrier PLC systems as well as that of the hybrid PLC-VLC system. Consequently, as deduced from the results, the models obtained utilizing the novel Metropolis-Hastings algorithm are more precise, near optimal model with parameter sets that are closer to the global maxima. Generally, the model results obtained in this thesis are relevant in enhancing transmission reliability on the PLC channel through the use of the models to improve the adopted modulation schemes, create adaptive modulation techniques, develop and evaluate forward error correction (FEC) codes such as a concatenation of Reed-Solomon and Permutation codes and other robust codes suitable for exploiting and mitigating noise impairments encountered on the low voltage NB-PLC channel. Furthermore, the recon gurable software de ned NB-PLC transceiver test-bed developed can be utilized for future measurement campaign as well as adapted for multiple-input and multiple-output (MIMO) PLC applications.MT201