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 this approach is a considerable reduction in the achievable bit error rate (BER) and the corresponding computational complexity of the sequential decoding algorithm (Pareto distribution). Furthermore, channel state information can easily be taken into account in this metric by applying log-likelihood ratios. Additional improvements are possible for systematic convolutional codes. Simulation results are presented for two different binary sources.
[1]
James L. Massey.
Variable-length codes and the Fano metric
,
1972,
IEEE Trans. Inf. Theory.
[2]
Robert Mario Fano,et al.
A heuristic discussion of probabilistic decoding
,
1963,
IEEE Trans. Inf. Theory.
[3]
Shu Lin,et al.
Error control coding : fundamentals and applications
,
1983
.
[4]
Joachim Hagenauer.
Soft is Better Than Hard
,
1994
.
[5]
Joachim Hagenauer.
Source-controlled channel decoding
,
1995,
IEEE Trans. Commun..
[6]
C. E. SHANNON,et al.
A mathematical theory of communication
,
1948,
MOCO.