A Comparison of ICF and Companding for Impulsive Noise Mitigation in Powerline Communication Systems

In future smart cities, smart grid technologies which are usually enabled by Powerline Communication (PLC) techniques are required. However, data transmission over powerline channel traverses a non-Gaussian media due to the presence of Impulsive Noise (IN) operating at the frequencies of PLC system which can be deployed using the IEEE 1901, that uses Orthogonal Frequency Division Multiplexing (OFDM). These OFDM signals have asymmetric amplitude distribution, which makes it difficult to identify and mitigate the IN presence. Converting the amplitude distribution to a uniform distribution can enhance the ability to mitigate IN when nonlinear IN mitigation techniques such as blanking is applied. In this study, we apply Iterative Clipping and Filtering (ICF) and companding schemes which are Peak-to-Average Power Ratio (PAPR) reduction techniques to enable symmetric amplitude distribution of the OFDM signals. With an optimization search for the optimal blanking amplitude for the two PAPR reduction schemes. Results show that companding scheme achieves 4dB gain in terms of received signal-to-noise ratio better than ICF after the blanking was used to remove the IN

Waveform clipping in FSK modulated signal to combat impulse noise

Abstract: This article presents results on the pre-processing (clipping/nulling) of impulse noise corrupted signal that is digitally modulated. The novelty of the article is in performing the clipping technique on the waveform of the digitally modulated signal as opposed to working with the constellation of the modulated signal. We present bit error rate performance results of Frequency Shift Keying (FSK) modulation in the presence of impulse noise and AWGN, when clipping is performed. We furthermore, develop closed-form expressions for the bit error rates of FSK modulation in the presence of both AWGN and impulse noise, when clipping of the received signal has been performed

On Companding and Optimization of OFDM Signals for Mitigating Impulsive Noise in Power-line Communication Systems

Generally, the probability density function (PDF) of orthogonal frequency division multiplexing (OFDM) signal amplitudes follow the Rayleigh distribution, thus, it is difficult to correctly predict the existence of impulsive noise (IN) in powerline communication (PLC) systems. Compressing and expanding the amplitudes of some of these OFDM signals, usually referred to as companding, is a peak-to-average power ratio (PAPR) reduction technique that distorts the amplitudes of OFDM signals towards a uniform distribution. We suggest its application in PLC systems such as IEEE 1901 powerline standard (which uses OFDM) to reduce the impacts of IN. This is because the PLC channel picks up impulsive interference that the conventional OFDM driver cannot combat. We explore, therefore, five widely used companding schemes that convert the OFDM signal amplitude distribution to uniform distribution to avail the mitigation of IN in PLC system receivers by blanking, clipping and their hybrid (clipping-blanking). We also apply nonlinear optimization search to find the optimal mitigation thresholds and results show significant improvement in the output signal-to-noise ratio (SNR) for all companding transforms considered of up to 4 dB SNR gain. It follows that the conventional PDF leads to false IN detection which diminishes the output SNR when any of the above three nonlinear memoryless mitigation schemes is applied

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

Nonlinear MMSE Equalizer for Impulsive Noise Mitigation in OFDM-Based Communications

© 2019 IEEE. Destructive effects of impulsive noise has been broadly observed not only in wireless communication systems but also in power-line communications. Impulsive noise is a common impediment in orthogonal frequency division multiplexing (OFDM) based communication systems for industry applications. This non-Gaussian noise degrades the performance of conventional equalizers and, hence, elicit a modified version of the equalizer that fits the non-Gaussian description of the noise. This letter proposes a nonlinear minimum mean square error equalizer for OFDM systems where the characteristics of the added noise to the system is known. The soft values were obtained based on the derivation of the equalizer for a memory-less channel impaired with impulsive noise. Obtaining such values are required for the implementation of a turbo-equalization scheme. The validity of such an equalizer is tested through simulations and the result of simulations shows that the nonlinear equalizer is successful in combating the effect of an impulsive noise. Thus, the turbo-coded OFDM system shows a significant boost at low signal-to-noise ratios