SEQUENTIAL-DECODING USING A-PRIORI INFORMATION

A metric for sequential decoding, based on the well known Fano metric, is proposed. It is suitable for using a priori information about the source bit probability in addition to soft inputs. The advantage of th is approach is a considerable reduction in the achievable bit error ra te (BER) and the corresponding computational complexity of the sequent ial decoding algorithm (Pareto distribution). Furthermore, channel sta te information can easily be taken into account in this metric by appl ying log-likelihood ratios. Additional improvements are possible for s ystematic convolutional codes. Simulation results are presented for tw o different binary sources.