Maximum likelihood sequence estimation (MLSE) in the shape of the Viterbi algorithm, although a strictly hard-output approach, is utilized for iterative decoding of turbo codes. It is a practical alternative when decoding complexity and speed may be traded for performance.

This work addresses the problem of decoding turbo convolutional codes. In particular, it is concerned with the question of how maximum likelihood sequence estimation (MLSE), in the shape of the Viterbi algorithm (VA), can be utilized in the framework of turbo decoding. It is shown that the conventional VA, which is a soft-input hard-output decoder, can be used for iterative decoding of turbo codes. Moreover, it is demonstrated how the VA can be used for obtaining accurate BER estimation as well as an effective stopping criterion.