Abstract

Algorithms developed with a Gaussian noise assumption perform poorly in impulsive noise, such as that described by the symmetric alpha-stable (S-alpha-S) distribution. We investigate the performance of antipodal signaling and Viterbi decoding of convolutional codes in S-alpha-S noise. We demonstrate that the p-norm branch metric is robust in S-alpha-S noise.