Syndrome based block decoding of convolutional codes

Abstract

A block processing approach for decoding of convolutional codes is proposed. The approach is based on the fact that it is possible for Scarce-State-Transition decoding and syndrome decoding to determine the probability of a certain trellis state before the actual decoding happens. This allows the separation of the received sequence into independant blocks with known initial and final states, thus making overlapping or modifications of the encoder or the information stream unnecessary. The proposed scheme offers potentials for both parallelization and reduction of power consumption.