PLC Performance Analysis Assuming BPSK Modulation Over Nakagami- $m$ Additive Noise

Performance Evaluation of PLC 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.

PLC Performance Analysis Over Rayleigh Fading Channel Under Nakagami- $m$ Additive Noise

Abstract: Power line communication (PLC) utilizes power lines for transmission of power as well as data transmission. It is an emerging field of communication for the home area network of smart grid. The performance of a PLC system is significantly affected by the additive and multiplicative power line noises; the additive noises are of two types, namely background noise and impulsive noise. Whereas, the multiplicative PLC noise leads to fading in the received signal strength. This paper provides the performance analysis of a PLC system over Rayleigh fading channel under Nakagami- $m$ distributed additive background noise assuming binary phase shift keying modulation scheme. The probability density function of the decision variable is derived. We obtain a numerically computable expression of the analytical average bit error rate of the considered system. The closed-form expression of the outage probability of the PLC system is also computed. Simulation results closely verify the validity of the derived analytical expressions.

Differential Chaos Shift Keying: A Robust Modulation Scheme for Power-Line Communications

Abstract: The past few years have witnessed a tremendous development in power-line communications (PLCs) for the realization of smart grids. Since power lines were not originally intended for conveying high-frequency signals, any communication over these lines would be exposed to severe adversarial factors, such as interference, impulsive, and phase noise. This elucidates the importance of employing robust modulation techniques and motivates research in this direction. Indeed, the aim of this brief is to propose a differential chaos shift keying (DCSK) modulation scheme as a potential candidate for smart grid communication networks. This DCSK class of noncoherent modulation is very robust against linear and nonlinear channel distortions. More importantly, the demodulation process can be carried out without any channel estimator at the receiver side. In this work, we analyze the bit error rate performance of DCSK over multipath PLC channels in which phase, background, and impulsive noise are present. A simulator is developed to verify the performance of the proposed DCSK against direct sequence code division multiple access and direct sequence differential phase shift keying. The results presented in this work prove the advantages of this low-cost noncoherent modulation technique for PLC systems over its rivals.

Learning-Based Signal Detection for MIMO Systems With Unknown Noise Statistics

Abstract: This paper aims to devise a generalized maximum likelihood (ML) estimator to robustly detect signals with unknown noise statistics in multiple-input multiple-output (MIMO) systems. In practice, there is little or even no statistical knowledge on the system noise, which in many cases is non-Gaussian, impulsive and not analyzable. Existing detection methods have mainly focused on specific noise models, which are not robust enough with unknown noise statistics. To tackle this issue, we propose a novel ML detection framework to effectively recover the desired signal. Our framework is a fully probabilistic one that can efficiently approximate the unknown noise distribution through a normalizing flow. Importantly, this framework is driven by an unsupervised learning approach, where only the noise samples are required. To reduce the computational complexity, we further present a low-complexity version of the framework, by utilizing an initial estimation to reduce the search space. Simulation results show that our framework outperforms other existing algorithms in terms of bit error rate (BER) in non-analytical noise environments, while it can reach the ML performance bound in analytical noise environments.

Performance Analysis of a Dual-Hop Wireless-Power Line Mixed Cooperative System

Abstract: Wireless communications and power line communications (PLC) are essential components for smart grid communications. This paper analyses the performance of a dual-hop wireless-power line mixed communication setup employing a decode-and-forward relay in terms of analytical average bit error rate (BER), outage probability, and average channel capacity. The Nakagami- $m$ distribution captures the wireless channel fading; whereas the PLC channel gain is characterized by the Log-normal distribution. The additive PLC channel noise is assumed to be Bernoulli-Gaussian distributed. Approximate closed-form expression of the average BER and exact closed-form expression of the outage probability are derived for the considered system. Further, we obtain an approximate closed-form expression of the capacity of the wireless-power line mixed system in terms of the Meijer-G function. It is observed that the system performance deteriorates as the impulsive noise index and the arrival probability of the impulsive component of the PLC additive noise increase.

Modeling and analysis of noise effects on broadband power-line communications

Abstract: Power line noise is known to affect the performance of broadband power-line communications significantly. This paper presents a frequency-domain approach to characterize and model the statistical variation of power-line noise. The model considers both the background noise and the impulsive noise. The background noise model is based on statistical analysis of the results from two long-term measurements of noise spectrum conducted at two separate sites of a laboratory and a residential apartment. On the other hand, the impulsive noise model is obtained by direct measurements from the noise sources (i.e., various electrical household appliances). The amount of impulse noise reaching a power-line communications (PLC) receiver can then be determined with consideration of the channel transfer characteristics between the noise sources and the PLC receiver. Using these noise models, the performance of two major classes of digital modulation schemes, namely single-carrier modulation and multicarrier modulation, are analyzed and compared. It is found that the multicarrier scheme performs better than the single-carrier scheme when subjected to the observed power-line noise with non-Gaussian statistics.

Modeling of transfer Characteristics for the broadband power line communication channel

Abstract: This paper presents a novel approach to model the transfer function of electrical power lines for broadband power line communication. In this approach, the power line is approximated as a transmission line and the two intrinsic parameters, the characteristic impedance and the propagation constants, are derived based on the lumped-element circuit model. Using these intrinsic parameters, the transfer characteristics for a N-branch power distribution network are derived based on the scattering matrix method. Detail derivation of this line model is given in this paper. The model has been verified with practical measurements conducted on actual power networks. It is demonstrated that the model accurately determine the line characteristics under different network configuration and when different household appliances are connected.

Power line communications

Abstract: This article overviews the power line communication, which is originally devised to transmit electric power from a small number of sources to a large number of sinks. Initially the first data transmission were over power lines were primarily done only to protect sections of the power distribution system in case of faults. This paper also studies the performance of power lines for high bit rate applications. DMT technology is adopted by the homeplug standard can theoretically provide data rates of 100Mb/s. However, products based on the standard only have achieved data rates up to 14 Mb/s. To protect against the severe noisy conditions and fading in the powerline channel, very high levels of error control coding need to be provided. The efforts of the homeplug alliance and home networking technology's growth in the US portend a very bright future for DMT-based PLC home networking.

Power line communications: an overview

Abstract: We give a systems level overview of power line communications. Topics covered, include feasible applications of power line communications, and the impact of the currently evolving international standards on power line communications. The power line communications channel is discussed at some length. Existing communications systems and solutions are discussed. The results of some measurements on the channel, are presented.

An Overview of Comonotonicity and Its Applications in Finance and Insurance

Abstract: Over the last decade, it has been shown that the concept of comonotonicity is a helpful tool for solving several research and practical problems in the domain of finance and insurance. In this chapter, we give an extensive bibliographic overview—without claiming to be complete—of the developments of the theory of comonotonicity and its applications, with an emphasis on the achievements in the period 2004–2010. These applications range from pricing and hedging of derivatives over risk management to life insurance.