  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 this context,
the traditional matched filter construction is modified to ensure
distortionless processing of the desired signal. The performance improvement of
the proposed ACDL is due to the fact that unlike other nonlinear methods, the
ACDL is implemented in the analog domain where the outliers are still broadband
and distinguishable. Simulation results in PRIME (OFDM-based narrowband PLC
system) demonstrate the superior BER performance of ACDL relative to other
nonlinear approaches such as blanking and clipping in impulsive noise
environments.
