Practical Implementation of Adaptive Analog Nonlinear Filtering For Impulsive Noise Mitigation
Reza Barazideh, Alexei V. Nikitin, Balasubramaniam Natarajan

TL;DR
This paper presents a practical analog nonlinear filter, ACDL, that adaptively detects and mitigates impulsive noise in OFDM-based powerline communication, improving signal quality and BER performance.
Contribution
Introduction of the Adaptive Canonical Differential Limiter (ACDL), a novel analog nonlinear filter combining CMTF and QTFs for real-time impulsive noise mitigation.
Findings
ACDL outperforms traditional nonlinear methods like blanking and clipping.
Simulation shows significant BER improvement in impulsive noise environments.
ACDL maintains linear behavior when no impulsive noise is present.
Abstract
It is well known that the performance of OFDM-based Powerline Communication (PLC) systems is impacted by impulsive noise. In this work, we propose a practical blind adaptive analog nonlinear filter to efficiently detect and mitigate impulsive noise. Specially, we design an Adaptive Canonical Differential Limiter (ACDL) which is constructed from a Clipped Mean Tracking Filter (CMTF) and Quartile Tracking Filters (QTFs). The QTFs help to determine a real-time range that excludes outliers. This range is fed into the CMTF which is responsible for mitigating impulsive noise. The CMTF is a nonlinear analog filter and its nonlinearity is controlled by the aforementioned range. Proper selection of this range ensures the improvement of the desired signal quality in impulsive environment. It is important to note that the proposed ACDL behaves like a linear filter in case of no impulsive noise. In…
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