  An Adaptive Nonlinear Differential Limiter (ANDL) is proposed in this paper
to efficiently alleviate the impact of impulsive noise (IN) in a communication
system. Unlike existing nonlinear methods, the ANDL is implemented in the
analog domain where the broader acquisition bandwidth makes outliers more
detectable and consequently it is easier to remove them. While the proposed
ANDL behaves like a linear filter when there is no outlier, it exhibits
intermittent nonlinearity in response to IN. Therefore, the structure of the
matched filter in the receiver is modified to compensate the filtering effect
of the ANDL in the linear regime. In this paper, we quantify the performance of
the ANDL by deriving a closed-form analytical bound for the average
signal-to-noise ratio (SNR) at the output of the filter. The calculation is
based on the idea that the ANDL can be perceived as a time-variant linear
filter whose bandwidth is modified based on the intensity of the IN. In
addition, by linearizing the filter time parameter variations, we treat the
ANDL as a set of linear filters where the exact operating filter at a given
time depends upon the magnitude of the outliers. The theoretical average bit
error rate (BER) is validated through simulations and the performance gains
relative to classical methods such as blanking and clipping are quantified.
