Maximum-Likelihood Decoding of Binary Convolutional Codes on Band-Limited Satellite Channels

Viterbi decoding of binary convolutional codes on bandlimited channels exhibiting intersymbol interference is considered, and a maximum likelihood sequence estimator algorithm is derived. This algorithm might be applied either to increase the allowable data rate for a fixed power transmitter or to reduce the required power for a fixed data rate. Upper and lower bounds on the bit error rate performance of several codes are found for selected values of the ratio of information rate to channel bandwidth, and results are compared against both conventional equalization techniques and the Shannon capacity limit. Results indicate that this algorithm can provide the power saving associated with low rate (highly redundant) codes without suffering the noise enhancement of linear equalization techniques.