Joint Erasure Marking and List Viterbi Algorithm for Decoding in Unknown Non-Gaussian Noise

In many real-world communication systems, the channel noise is non-Gaussian due to the presence of impulsive noise as well as the background Gaussian noise. In such situations, the conventional Euclidean distance based decoder may suffer from the problem of severe metric mismatch. To overcome the problem, we recently proposed the joint erasure marking and Viterbi algorithm (JEVA) as a robust trellis decoder that does not require an estimate of the impulsive noise distribution. In this work, two ways to further improve JEVA are presented for systems with an error detecting code. Specifically, the JEVA is integrated with the list Viterbi algorithm (LVA) to form the two-dimensional joint erasure marking and list Viterbi algorithm (JELVA) and the switched JELVA, respectively. By combining the respective strengths of the JEVA and the LVA, the integrated decoding schemes are able to achieve significant performance gains over the original JEVA and achieve a wide range of performance-complexity-delay tradeoffs.