  Impulsive noise is a major impediment to orthogonal frequency-division
multiplexing (OFDM) based underwater acoustic (UWA) communications. In this
work, we evaluate the performance of a memoryless analog nonlinear preprocessor
(MANP) that is used to mitigate outliers. The proposed MANP exhibits
intermittent nonlinearity only in the presence of the impulsive noise and
suppresses the power of outliers based on their amplitudes. Since the outliers
are distinguishable in the analog domain prior to anti-aliasing filtering, the
MANP outperforms its digital counterparts in all scenarios. Experimental
results using data collected in an under-ice environment, demonstrate the
superior BER performance of our approach relative to classical nonlinear
approaches such as blanking and clipping.
