Cutoff Rates for Convolutional Codes on Gaussian Channels Impaired by Peak and Variance Constrained Interference

In this paper, we investigate the performance of convolutional coding with soft-decision Viterbi decoding on channels impaired by both additive Gaussian noise and various types of non-Gaussian interference. In particular, we derive a closed-form expression for the computational cutoff rate, R, assuming a Viterbe decoder designed for optimality in the presence of additive Gaussian noise only, that is, the receiver makes no attempt to compensate for the statistics of the non-Gaussian interference. Under these conditions, we show that R is easily expressed in terms of the characteristic function of the interference.