Generalized Feedback Decoding of Convolutional Codes

The use of convolutional codes with feedback decoding is a common error-correction technique in simple communication systems. A drawback of conventional feedback decoding is the limitation to a class of self-orthogonal codes which, in general, are nonoptimum. Based on distance properties of the utilized code and test-error pattern analysis, we propose generalized feedback decoding which does not have the abovementioned limitation. This is minimum distance decoding and can be applied to any convolutional code while still maintaining its simplicity. Therefore, it has the advantage of being easily adopted in existing systems. We can use the relatively complicated Viterbi or sequential decoders in larger terminals and, with the same code, use the proposed decoders in smaller terminals; otherwise, both large and small terminals must utilize the same type of decoder. The proposed decoding scheme could also be used to simplify and speed up sequential decoding. In addition, comparisons of the proposed decoder with other feedback decoders are presented.