Power line communications over time-varying frequency-selective power line channels for smart home applications

Many countries in the world are developing the next generation power grid, the smart grid, to combat the ongoing severe environmental problems and achieve e�cient use of the electricity power grid. Smart metering is an enabling technology in the smart grid to address the energy wasting problem. It monitors and optimises the power consumption of consumers' devices and appliances. To ensure proper operation of smart metering, a reliable communication infrastructure plays a crucial role. Power line communication (PLC) is regarded as a promising candidate that will ful�l the requirements of smart grid applications. It is also the only wired technology which has a deployment cost comparable to wireless communication. PLC is most commonly used in the low-voltage (LV) power network which includes indoor power networks and the outdoor LV distribution networks. In this thesis we consider using PLC in the indoor power network to support the communication between the smart meter and a variety of appliances that are connected to the network. Power line communication (PLC) system design in indoor power network is challenging due to a variety of channel impairments, such as time-varying frequency-selective channel and complex impulsive noise scenarios. Among these impairments, the timevarying channel behaviour is an interesting topic that hasn't been thoroughly investigated. Therefore, in this thesis we focus on investigating this behaviour and developing a low-cost but reliable PLC system that is able to support smart metering applications in indoor environments. To aid the study and design of such a system, the characterisation and modelling of indoor power line channel are extensively investigated in this thesis. In addition, a exible simulation tool that is able to generate random time-varying indoor power line channel realisations is demonstrated. Orthogonal frequency division modulation (OFDM) is commonly used in existing PLC standards. However, when it is adopted for time-varying power line channels, it may experience signi�cant intercarrier interference (ICI) due to the Doppler spreading caused by channel time variation. Our investigation on the performance of an ordinary OFDM system over time-varying power line channel reveals that if ICI is not properly compensated, the system may su�er from severe performance loss. We also investigate the performance of some linear equalisers including zero forcing (ZF), minimum mean squared error (MMSE) and banded equalisers. Among them, banded equalisers provide the best tradeo� between complexity and performance. For a better tradeo� between complexity and performance, time-domain receiver windowing is usually applied together with banded equalisers. This subject has been well investigated for wireless communication, but not for PLC. In this thesis, we investigate the performance of some well-known receiver window design criteria that was developed for wireless communication for time-varying power line channels. It is found that these criteria do not work well over time-varying power line channels. Therefore, to �ll this gap, we propose an alternative window design criterion in this thesis. Simulations have shown that our proposal outperforms the other criteria

Inferring Power Grid Information with Power Line Communications: Review and Insights

High-frequency signals were widely studied in the last decade to identify grid and channel conditions in PLNs. PLMs operating on the grid's physical layer are capable of transmitting such signals to infer information about the grid. Hence, PLC is a suitable communication technology for SG applications, especially suited for grid monitoring and surveillance. In this paper, we provide several contributions: 1) a classification of PLC-based applications; 2) a taxonomy of the related methodologies; 3) a review of the literature in the area of PLC Grid Information Inference (GII); and, insights that can be leveraged to further advance the field. We found research contributions addressing PLMs for three main PLC-GII applications: topology inference, anomaly detection, and physical layer key generation. In addition, various PLC-GII measurement, processing, and analysis approaches were found to provide distinctive features in measurement resolution, computation complexity, and analysis accuracy. We utilize the outcome of our review to shed light on the current limitations of the research contributions and suggest future research directions in this field.Comment: IEEE Communication Surveys and Tutorials Journa

Radio Access Network Backhauling Using Power Line Communications

Nowadays, radio access networks (RANs) are moving toward a small cell-based paradigm, where the macro-cell antennas are aided by additional ones with lower coverage capabilities. This paradigm shift brings a new problem into the equation: a backhaul link is needed to carry the traffic from the small cell base stations to the network gateway. Currently, both wired and wireless solutions exist, but none is universally considered optimal. Power line communications (PLC) can be considered as a broadband access solution for this backhaul branch. Recent developments helped to push PLC performances to a point where state-of-the-art solutions can achieve very high-speed data transfers. Aided by traffic generation-based simulations, we will show how the PLC technology can be assessed for the described application. The reader will be guided through the process by discussing small cell networks, the power line infrastructure and basics of traffic generation modeling. The chapter will then discuss a quality-of-service (QoS)-driven analysis and use numerical results to show how requirements can be defined for the backhauling technology. Overall, this chapter will address how PLC and small cell network technologies can be brought together in a unified model to foster future small cell technology

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

Power line communication (PLC) channel measurements and characterization.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.The potential of the power line to transport both power and communication signals simultaneously has been realized and practiced for over a century, dating back to the 1900’s. Since the key aspect of power line communications being its expansivity, its implementations were largely as a retrofit technology. This motivation of power line communication is typical for low-, medium-, and high voltage distribution networks. Beyond the “last mile” part, there’s an uprising appeal for intra-building networks currently targeted for home automation (smart homes/buildings) and in-building networking. The optimum use of the existing power line channels has been a focus area for researchers and designers, with the inherent channel hostility proving a serious drawback for high speed data communications. The low-voltage electrical network has unpredictable noise sources, moreover it has two other main disadvantages as a communication channel. The first short coming has to do with the unknown characteristics of the power cable and topology of the network, the second arises from the time-dependent fluctuation of the impedance level of the power line as the loads are switched into and out of the power line network in an unpredictable manner. These factors determine the behaviour of the power line channel when a high frequency signal is impressed on it. This study has shown that the behaviour of indoor power line channels can be captured using a multipath based model even with limited qualitative and/or quantitative knowledge of the network topology. This model is suitable for typical indoor power line channels where knowledge of the topology is near impossible. Some of the feed parameters are obtained through measurements. With sufficient adjustment of control parameters, this model was successfully validated using sample measured channels from the numerous measurements. Through noise measurements, this study has established that impulsive noise is the rifest in the frequency band of interest. The impulsive energy rises well above background noise, which translates to possible data “black outs”. The statistics of the components of this noise are presented. A model of sufficient simplicity is used to facilitate the qualitative description of the background noise through its power spectral density. Two descriptions are provided in terms of the worst and best case scenarios of the background noise occurrences. The model has a good macroscopic capture of the noise power spectral density, with narrow-band interference visible for the worst case noise. Due to the multipath nature of the power line channel, this study also presents the dispersive characteristics of the power line as a communication channel. The power delay profile is used to determine parameters such as first arrival delay, mean excess delay, root mean square delay spread and maximum delay spread. The statistics of these parameters are presented. Also, the coherence bandwidth of power line channels is studied and its relationship with the rms delay spread is developed. It is in view of this work that further research in power line communication and related topics shall be inspired

Characterization and modeling of the channel and noise for broadband indoor Power Line Communication (PLC) networks.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2016Power Line Communication (PLC) is an interesting approach in establishing last mile broadband access especially in rural areas. PLC provides an already existing medium for broadband internet connectivity as well as monitoring and control functions for both industrial and indoor usage. PLC network is the most ubiquitous network in the world reaching every home. However, it presents a channel that is inherently hostile in nature when used for communication purposes. This hostility is due to the many problematic characteristics of the PLC from a data communications’ perspective. They include multipath propagation due to multiple reflections resulting from impedance mismatches and cable joints, as well as the various types of noise inherent in the channel. Apart from wireless technologies, current high data rate services such as high speed internet are provided through optical fibre links, Ethernet, and VDSL (very-high-bit-rate digital subscriber line) technology. The deployment of a wired network is costly and demands physical effort. The transmission of high frequency signals over power lines, known as power line communications (PLC), plays an important role in contributing towards global goals for broadband services inside the home and office. In this thesis we aim to contribute to this ideal by presenting a powerline channel modeling approach which describes a powerline network as a lattice structure. In a lattice structure, a signal propagates from one end into a network of boundaries (branches) through numerous paths characterized by different reflection/transmission properties. Due to theoretically infinite number of reflections likely to be experienced by a propagating wave, we determine the optimum number of paths required for meaningful contribution towards the overall signal level at the receiver. The propagation parameters are obtained through measurements and other model parameters are derived from deterministic power system. It is observed that the notch positions in the transfer characteristics are associated with the branch lengths in the network. Short branches will result in fewer notches in a fixed bandwidth as compared to longer branches. Generally, the channel attenuation increase with network size in terms of number of branches. The proposed model compares well with experimental data. This work presents another alternative approach to model the transfer characteristics of power lines for broadband power line communication. The model is developed by considering the power line to be a two-wire transmission line and the theory of transverse electromagnetic (TEM) wave propagation. The characteristic impedance and attenuation constant of the power line are determined through measurements. These parameters are used in model simplification and determination of other model parameters for typical indoor multi-tapped transmission line system. The transfer function of the PLC channel is determined by considering the branching sections as parallel resonant circuits (PRC) attached to the main line. The model is evaluated through comparison with measured transfer characteristics of known topologies and it is in good agreement with measurements. Apart from the harsh topology of power line networks, the presence of electrical appliances further aggravates the channel conditions by injecting various types of noises into the system. This thesis also discusses the process of estimating powerline communication (PLC) asynchronous impulsive noise volatility by studying the conditional variance of the noise time series residuals. In our approach, we use the Generalized Autoregressive Conditional Heteroskedastic (GARCH) models on the basis that in our observations, the noise time series residuals indicate heteroskedasticity. By performing an ordinary least squares (OLS) regression of the noise data, the empirical results show that the conditional variance process is highly persistent in the residuals. The variance of the error terms are not uniform, in fact, the error terms are larger at some portions of the data than at other time instances. Thus, PLC impulsive noise often exhibit volatility clustering where the noise time series is comprised of periods of high volatility followed by periods of high volatility and periods of low volatility followed by periods of low volatility. The burstiness of PLC impulsive noise is therefore not spread randomly across the time period, but instead has a degree of autocorrelation. This provides evidence of time-varying conditional second order moment of the noise time series. Based on these properties, the noise time series data is said to suffer from heteroskedasticity. GARCH models addresses the deficiencies of common regression models such as Autoregressive Moving Average (ARMA) which models the conditional expectation of a process given the past, but regards the past conditional variances to be constant. In our approach, we predict the time-varying volatility by using past time-varying variances in the error terms of the noise data series. Subsequent variances are predicted as a weighted average of past squared residuals with declining weights that never completely diminish. The parameter estimates of the model indicates a high degree of persistence in conditional volatility of impulsive noise which is a strong evidence of explosive volatility. Parameter estimation of linear regression models usually employs least squares (LS) and maximum likelihood (ML) estimators. While maximum likelihood remains one of the best estimators within the classical statistics paradigm to date, it is highly reliant on the assumption about the joint probability distribution of the data for optimal results. In our work, we use the Generalized Method of Moments (GMM) to address the deficiencies of LS/ML in order to estimate the underlying data generating process (DGP). We use GMM as a statistical technique that incorporate observed noise data with the information in population moment conditions to determine estimates of unknown parameters of the underlying model. Periodic impulsive noise (short-term) has been measured, deseasonalized and modeled using GMM. The numerical results show that the model captures the noise process accurately. Usually, the impulsive signals originates from connected loads in an electrical power network can often be characterized as cyclostationary processes. A cyclostationary process is described as a non-stationary process whose statistics exhibit periodic time variation, and therefore can be described by virtue of its periodic order. The focus of this chapter centres on the utilization of cyclic spectral analysis technique for identification and analysis of the second-order periodicity (SOP) of time sequences like those which are generated by electrical loads connected in the vicinity of a power line communications receiver. Analysis of cyclic spectrum generally incorporates determining the random features besides the periodicity of impulsive noise, through the determination of the spectral correlation density (SCD). Its effectiveness on identifying and analysing cyclostationary noise is substantiated in this work by processing data collected at indoor low voltage sites

Characterization and modelling of the channel and noise for broadband indoor powerline communication (plc.) networks.

Masters degree. University of KwaZulu-Natal, Durban.Power Line Communication (PLC) is an interesting approach in establishing last mile broad band access especially in rural areas. PLC provides an already existing medium for broad band internet connectivity as well as monitoring and control functions for both industrial and indoor usage. PLC network is the most ubiquitous network in the world reaching every home. However, it presents a channel that is inherently hostile in nature when used for communication purposes. This hostility is due to the many problematic characteristics of the PLC from a data communications’ perspective. They include multipath propagation due to multiple reflections resulting from impedance mismatches and cable joints, as well as the various types of noise inherent in the channel. Apart from wireless technologies, current high data rate services such as high speed internet are provided through optical fibre links, Ethernet, and VDSL (very-high-bit-rate digital subscriber line) technology. The deployment of a wired network is costly and demands physical effort. The transmission of high frequency signals over power lines, known as power line communications (PLC), plays an important role in contributing towards global goals for broadband services inside the home and office. In this thesis we aim to contribute to this ideal by presenting a powerline channel modeling approach which describes a powerline network as a lattice structure. In a lattice structure, a signal propagates from one end into a network of boundaries (branches) through numerous paths characterized by different reflection/transmission properties. Due to theoretically infi nite number of reflections likely to be experienced by a propagating wave, we determine the optimum number of paths required for meaningful contribution towards the overall signal level at the receiver. The propagation parameters are obtained through measurements and other model parameters are derived from deterministic power system. It is observed that the notch positions in the transfer characteristics are associated with the branch lengths in the network. Short branches will result in fewer notches in a fixed bandwidth as compared to longer branches. Generally, the channel attenuation increase with network size in terms of number of branches. The proposed model compares well with experimental data. This work presents another alternative approach to model the transfer characteristics of power lines for broadband power line communication. The model is developed by considering the power line to be a two-wire transmission line and the theory of transverse electromagnetic (TEM) wave propagation. The characteristic impedance and attenuation constant of the power line v are determined through measurements. These parameters are used in model simplification and determination of other model parameters for typical indoor multi-tapped transmission line system. The transfer function of the PLC channel is determined by considering the branching sections as parallel resonant circuits (PRC) attached to the main line. The model is evaluated through comparison with measured transfer characteristics of known topologies and it is in good agreement with measurements. Apart from the harsh topology of power line networks, the presence of electrical appliances further aggravates the channel conditions by injecting various types of noises into the system. This thesis also discusses the process of estimating powerline communication (PLC) asynchronous impulsive noise volatility by studying the conditional variance of the noise time series residuals. In our approach, we use the Generalized Autoregressive Conditional Heteroskedastic (GARCH) models on the basis that in our observations, the noise time series residuals indicate heteroskedasticity. By per forming an ordinary least squares (OLS) regression of the noise data, the empirical results show that the conditional variance process is highly persistent in the residuals. The variance of the error terms are not uniform, in fact, the error terms are larger at some portions of the data than at other time instances. Thus, PLC impulsive noise often exhibit volatility clustering where the noise time series is comprised of periods of high volatility followed by periods of high volatility and periods of low volatility followed by periods of low volatility. The burstiness of PLC impulsive noise is therefore not spread randomly across the time period, but instead has a degree of autocorrelation. This provides evidence of time-varying conditional second order moment of the noise time series. Based on these properties, the noise time series data is said to suffer from heteroskedasticity. GARCH models addresses the deficiencies of common regression models such as Autoregressive Moving Average (ARMA) which models the conditional expectation of a process given the past, but regards the past conditional variances to be constant. In our approach, we predict the time-varying volatility by using past time-varying variances in the error terms of the noise data series. Subsequent variances are predicted as a weighted average of past squared residuals with declining weights that never completely diminish. The parameter estimates of the model indicates a high de gree of persistence in conditional volatility of impulsive noise which is a strong evidence of explosive volatility. Parameter estimation of linear regression models usually employs least squares (LS) and maximum likelihood (ML) estimators. While maximum likelihood remains one of the best estimators within the classical statistics paradigm to date, it is highly reliant vi on the assumption about the joint probability distribution of the data for optimal results. In our work, we use the Generalized Method of Moments (GMM) to address the deficien cies of LS/ML in order to estimate the underlying data generating process (DGP). We use GMM as a statistical technique that incorporate observed noise data with the information in population moment conditions to determine estimates of unknown parameters of the under lying model. Periodic impulsive noise (short-term) has been measured, deseasonalized and modeled using GMM. The numerical results show that the model captures the noise process accurately. Usually, the impulsive signals originates from connected loads in an electrical power network can often be characterized as cyclostationary processes. A cyclostationary process is described as a non-stationary process whose statistics exhibit periodic time varia tion, and therefore can be described by virtue of its periodic order. The focus of this chapter centres on the utilization of cyclic spectral analysis technique for identification and analysis of the second-order periodicity (SOP) of time sequences like those which are generated by electrical loads connected in the vicinity of a power line communications receiver. Analysis of cyclic spectrum generally incorporates determining the random features besides the pe riodicity of impulsive noise, through the determination of the spectral correlation density (SCD). Its effectiveness on identifying and analysing cyclostationary noise is substantiated in this work by processing data collected at indoor low voltage sites

Channel characterization for broadband powerline communications.

Ph. D. University of KwaZulu-Natal, Durban 2014.The main limiting factor in broadband powerline communications is the presence of impedance discontinuities in the wired channel. This phenomenon is present in both outdoor and indoor powerline communication (PLCs) channels. It has been established that the impedance of the electrical loads and line branching are the main causes of impedance discontinuities in PLC channel networks. Accurate knowledge of the expected impedances of the corresponding discontinuity points would be vital in order to characterize the channel for signal transmission. However, the PLC channel network topologies lead to different branching structures. Additionally, the existence of a myriad of electrical loads, whose noise and impedance vary with frequency, are a motivation for a rigorous design methodology in order to achieve a pragmatic channel model. In order to develop such a channel model, an approach similar to the one applied in radio propagation channel modeling is adopted, where specific attenuation determined at a point is used in predicting the attenuation for the entire power cable length. Therefore, the powerline is modeled with the assumption of a randomly spread multitude of scatterers in the vicinity of the channel with only a sufficient number of impedance discontinuity points. The line is considered as a single homogeneous element with its length divided into a grid of small areas with dimensions that range from 0.5 to 3 mm. Thus, each small area transmits an echo and the forward scattered response gets to the receiver. With this approach, point specific attenuation along the line is proposed and used to derive the channel transfer function. Measurement results show that both the analytical specific attenuation model developed in this work and the channel transfer function are feasible novel ideas in PLC channel network characterization. It is seen from the measurements that the signal attenuation is directly proportional to the number of branches, and this is in line with the findings of previous researchers. A comparison between the measured values and the simulation results of the frequency response shows a very good agreement. The agreement demonstrates applicability of the models in a practical enviroment. Thus we conclude that the models developed do not require knowledge either of the link topology or the cable models but requires an extensive measurement campaign