Performance of Analog Nonlinear Filtering for Impulsive Noise Mitigation in OFDM-based PLC Systems

TL;DR

This paper introduces an adaptive nonlinear analog filter called ANDL that effectively mitigates impulsive noise in OFDM-based powerline communication systems, improving bit-error-rate without affecting the desired signal.

Contribution

The paper proposes a novel adaptive nonlinear differential limiter (ANDL) that is simple, noise-model agnostic, and compatible with existing filters for impulsive noise mitigation in OFDM PLC systems.

Findings

ANDL outperforms other methods in reducing BER under impulsive noise.

The proposed filter is blind to noise distribution, ensuring broad applicability.

Simulation results confirm significant performance improvements.

Abstract

Asynchronous and cyclostationary impulsive noise can severely impact the bit-error-rate (BER) of OFDM-based powerline communication systems. In this paper, we analyze an adaptive nonlinear analog front end filter that mitigates various types of impulsive noise without detrimental effects such as self-interference and out-of-band power leakage caused by other nonlinear approaches like clipping and blanking. Our proposed Adaptive Nonlinear Differential Limiter (ANDL) is constructed from a linear analog filter by applying a feedback-based nonlinearity, controlled by a single resolution parameter. We present a simple practical method to find the value of this resolution parameter that ensures the mitigation of impulsive without impacting the desired OFDM signal. Unlike many prior approaches for impulsive noise mitigation that assume a statistical noise model, ANDL is blind to the exact nature of the noise distribution, and is designed to be fully compatible with existing linear front end filters. We demonstrate the potency of ANDL by simulating the OFDM-based narrowband PLC compliant with the IEEE standards. We show that the proposed ANDL outperforms other approaches in reducing the BER in impulsive noise environments.