A time domain model of background noise for inhome PLC networks

International audienceMultiple-Input/Multiple-Output (MIMO) techniques have recently become an important research field for enhancing the performance of in-home Power Line Communication (PLC) systems by exploiting the additional Protective Earth wire. The development of such systems requires an accurate description of the channel noise. In this paper we have presented a model for PLC background noise based on an extensive set of measurements. We have adopted the framework of multivariate time series to model the PLC background noise.This paper employs the Vector Autoregressive (VAR) modeling technique to extract noise model parameters from the measured noise. We have verified the accuracy of the noise model by comparing time and frequency domain correlation of measured and modeled noises

Channel estimation and modeling of power line communication

This thesis deals with modeling of power line communication. A two-port network model is theoretically described. A substantial part is focused on the mathematical description of distribution network using the method, which uses chain parameter matrices describing the relation between input and output voltage and current of the twoport network. This method is used for modeling sample power line topology. Furthermore, taps length and taps impedance influence on the transfer functions for different topology are examined. In this thesis, a decision–directed method is proposed for channel estimation and equalization in Power line communication (PLC) based on orthogonal frequency division multiplexing (OFDM). This method does not require a priori knowledge on the power line. Simulations on a realistic indoor power-line system show that the method achieves very good channel estimation and equalization performances and that it is robust to impulsive noise and nonlinearities. Later multilayer perceptron (MLP) based algorithm called back propagation algorithm has been proposed in power line communication. The present method (back propagation algorithm) is a OFDM based model which exploited for the channel estimation. Simulations on a realistic indoor power-line system show that the results obtained from the channel estimation using present model are significantly improved when compared with competitive neural network. It is also noteworthy to mention that the computational complexity is decreased using the present algorith

Noise modeling for standard CENELEC A-band power line communication channel

Power line communications (PLC) usage of low-voltage electrical power supply network as a medium of communication provides an alternative for the telecommunication access and in-house communication. Historically, power lines were majorly used for controlling appliances, however, with recent technology advancements power lines are now able to compete favorably and successfully with other relatively stable home automation and networking technologies like fixed line and wireless. Regardless of the advantages PLC has to offer, like every other communication technology, it has its own technical challenges it must overcome to be fully deployed and maximize its full potential. Such challenges includes noise, which can originate from appliances connected across the network or can be coupled unto the network. Harmful interference to other wireless spectrum users such as broadcast stations, and signal attenuation are other challenges faced by usage of the power line as a communication medium. PLC suffers the risk of not living up to its full development as a reliable means of communication if proper understanding of the channel potential and characteristic is not known. Therefore, understanding of the channel potential and characteristics can be obtained through measurement and modeling of the PLC channel. This model and measurements of the channel characteristics can then be utilized in designing a good PLC system which is able to withstand and mitigate the effect of the different kind of noise and disturbance present on the PLC network. This research therefore aims at formulizing and modeling the error pattern/behavior of noise and disturbances of an in-house CENELEC A-band based on experimental measurements. This is achieved by carrying out a real time experimental measurement of noise over a complete day to show the noise behavior. Error sequences are then generated from the measurement for the different classes of noise present on the CENELEC A-band and the use of Fritchman model, a Markovian chain model, is then employed to model the CENELEC A-band channel. This involves the use of Baum-Welch algorithm (an iterative algorithm) to estimate the model parameters of the three-state Markovian Fritchman model assumed. This precise channel model can then be used to design a good PLC system and facilitate the design of efficient coding and/or modulation schemes to enhance reliable communication on the PLC network. Therefore, answering the question of “how to formulize and model the error pattern/behavior of noise and disturbances of an in-house CENELEC A-band based on experimental measurements”

A flexible statistical framework for the characterization and modelling of noise in powerline communication channels.

Doctor of Philosophy in Electronic Engineering.One communication medium that has received a lot of interest in recent years is the power line channel, especially for the delivery of broadband content. This channel has been traditionally used to carry electrical power only. But with the recent advancements in digital signal processing, it is now possible to realize communications through the power grid, both in narrowband and broadband. The use of the power line network for telecommunication purposes constitutes what is referred to as powerline carrier communications or simply powerline communications (PLC). The biggest incentive for PLC technology use is the fact that the power line network is already in place, which greatly reduces the communication network set up cost, since no new cabling layout is required. PLC technology is widely applied in home networking, broadband internet provision and smart grid solutions. However, the PLC channel presents a very hostile communication environment. And as such, no consideration has been made in the design of traditional power line network to accommodate communication services. Of all the PLC channel impairments which include frequency-dependent attenuation, frequency selectivity, multipath and noise, noise is the biggest threat to communication signals. This noise manifests itself in form of coloured background noise, narrowband interference and impulsive noise. A thorough understanding of this noise distribution is therefore crucial for the design of a reliable and high performing PLC system. A proper understanding of the noise characteristics in the PLC channel can only be realized through noise measurements in live power networks, and then analyzing and modeling the noise appropriately. Moreover, the noise scenario in power line networks is very complex and therefore cannot be modeled through mere analytical methods. Additionally, most of the models that have been proposed for the PLC noise previously are mere adaptations of the measured noise to some existing impulsive noise models. These earlier modeling approaches are also rigid and model the noise via a fixed set of parameters. In the introductory work in this thesis, a study of orthogonal frequency division multiplexing (OFDM) as the modulation of choice for PLC systems is presented. A thorough survey of the salient features of this modulation scheme that make it the perfect candidate for PLC modulation needs is presented. In the end, a performance analysis study on the impact of impulsive noise on an OFDM based binary phase shift keying (BPSK) system is done. This study differs from earlier ones in that its focus is on how the elementary parameters that define the impulsive noise affect the system, a departure from the usual norm of considering the overall noise distribution. This study focuses on the impact of interarrival times (IAT), pulse amplitudes as well as pulse widths, among other parameters. In the first part of the main work in this thesis, results of an intensive noise measurement campaign for indoor low voltage power line noise carried out in various power line networks, in the Department of Electrical, Electronic and Computer Engineering buildings at the University of KwaZulu-Natal, Howard campus are presented. The noise measurements are carried out in both time and frequency domains. Next, the noise measurements are then analyzed and modeled using two very flexible data modeling tools; nonparametric kernel density estimators and parametric alpha stable (α-stable) distributions. The kernel method’s ability to overcome all the shortcomings of the primitive histogram method makes it very attractive. In this method, the noise data structure is derived straight from the data itself, with no prior assumptions or restrictions on the data structure, thus effectively overcoming the rigidity associated with previous noise models for power line channels. As such, it results in density estimates that “hug” the measured density as much as possible. The models obtained using the kernel methods are therefore better than any parametric equivalent; something that can always be proven through goodness of fit tests. These models therefore form an excellent reference for parametric modeling of the power line noise. This work forms the author’s first main contribution to PLC research. As a demonstration of the kernel models suitability to act as a reference, parametric models of the noise distribution using the alpha stable (α-stable) distribution are also developed. This distribution is chosen due to its flexibility and ability to capture impulsiveness (long-tailed behaviour), such as the one found in power line noise. Stable distributions are characterized by long/fat tails than those of the Gaussian distribution, and that is the main reason why they are preferable here since the noise characteritics obtained in the kernel technique show visible long/heavy tailed behavior. A parameter estimation technique that is based on quantiles and another on the empirical characteristic function are employed in the extraction of the four parameters that define the characteristic function of the α-stable distribution. The application of the α-stable distribution in other signal processing problems has often been over-simplied by considering the symmetric alpha stable distribution, but in this thesis, the general α-stable distribution is used to model the power line noise. This is necessary so as to ensure that no features of the noise distribution are missed. All the models obtained are validated through error analysis and Chi-square fitness tests. This work forms the author’s second main contribution to PLC research. The author’s last contribution in this thesis is the development of an algorithm for the synthesis of the power line as a Levy stable stochastic process. The algorithm developed is then used to generate the PLC noise process for a random number of alpha stable noise samples using the alpha stable noise parameters obtained in the parametric modeling using stable distributions. This algorithm is generalized for all admissible values of alpha stable noise parameters and therefore results for a Levy stable Gaussian process are also presented for the same number of random noise samples for comparison purposes

Modeling and Link Performance Analysis of Busbar Distribution Systems for Narrowband PLC

Busbar distribution system is used as a modular infrastructure to carry electrical energy in low voltage grid. Due to the widespread usage in industrial areas, the power line communication possibilities should be investigated in terms of smart grid concept. This paper addresses modeling of the busbar distribution system as a transmission line and gives some suggestions on the link performance for narrowband power line communication for the first time in literature. Firstly, S-parameters of different current level busbars were measured up to 500 kHz for all possible two-port signal paths. The utilization of the frequency-dependent model was proposed to extract transmission line characteristics to eliminate the unwanted measurement effects. Particle swarm algorithm was used to optimize the model parameters with a good agreement between measured and simulated S-parameters. Additionally, link performance of busbar distribution system as a power line communication channel at 3 kHz-148.5 kHz band was examined for frequency shift keying and phase shift keying modulations under different network configurations such as varying busbar type, the line length between transmitter and receiver, branch number, and terminating load impedance. Obtained results were presented as bit-error-rate vs. signal to noise ratio graphs

Statistical Characterization of Indian Residential Networks for Powerline Communication

Despite different powerline channel modeling techniques, developed so far, there are still specific dynamic, varying parameters (viz. the random load variation and inconsistent electrical wiring) to be studied for a valid and reliable power line communication (PLC) model. Statistical characterization of PLC channel may provide the required background for refinement of these existent models. In this paper, the Indian residential networks are statistically analyzed in the frequency range of 1-100 MHz. This also includes the comprehensive analysis of line impedance, stationary noise, channel capacity and average channel gain. From the measurements, the noise spectrum density is found to be less than -90 dBm at a frequency less than 1 MHz and is almost constant after 70 MHz. The minimum and maximum channel capacity of the network is 71.5 Mbps and 97.7 Mbps respectively. The Average channel gain is estimated at -30 dB. The paper also reviews the channel transfer function developed by top-down and bottom-top approaches.  Finally, some additional factors influencing the PLC channel are also discussed

Stochastic Geometry Modeling and Analysis of Multi-Tier Millimeter Wave Cellular Networks

In this paper, a new mathematical framework to the analysis of millimeter wave cellular networks is introduced. Its peculiarity lies in considering realistic path-loss and blockage models, which are derived from recently reported experimental data. The path-loss model accounts for different distributions of line-of-sight and non-line-of-sight propagation conditions and the blockage model includes an outage state that provides a better representation of the outage possibilities of millimeter wave communications. By modeling the locations of the base stations as points of a Poisson point process and by relying on a noise-limited approximation for typical millimeter wave network deployments, simple and exact integral as well as approximated and closed-form formulas for computing the coverage probability and the average rate are obtained. With the aid of Monte Carlo simulations, the noise-limited approximation is shown to be sufficiently accurate for typical network densities. The proposed mathematical framework is applicable to cell association criteria based on the smallest path-loss and on the highest received power. It accounts for beamforming alignment errors and for multi-tier cellular network deployments. Numerical results confirm that sufficiently dense millimeter wave cellular networks are capable of outperforming micro wave cellular networks, both in terms of coverage probability and average rate.Comment: Submitted to IEEE Transactions on Wireless Communication

Modeling Of Power Line Communication Channel For Automatic Meter Reading System With LDPC Codes

In this era of modernization, one of the promising emerging technologies is Power Line Communication (PLC) system. In previous research fields, modeling of PLC channel, mostly for indoor applications has been studied. However, the need to study that for outdoor applications, such as the Automatic Meter Reading (AMR) systems is also vital. Moreover, standardization bodies have considered the use of LDPC codes restricted for indoor systems. Thus, in this paper, not only we model the PLC channel based on AMR applications, but also, we apply LDPC coding scheme to the system. To accomplish the objectives, firstly, we model the PLC-AMR channel, which includes multipath phenomenon. Additionally, PLC noise, usually occurring in the channel, is modeled. The modulation technique applied is BPSK and the performance of the system with varying load impedances is compared. The coded system consists of irregular LDPC codes, with two different constructions of the Parity-Check matrix, namely that by Radford Neal and reduced size of DVBS2. The performances of respective systems are then compared. Using LDPC by Radford Neal, the performances are analyzed with varied code rates

State-of-the-art in Power Line Communications: from the Applications to the Medium

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201