Efficient SOVA decoding and enhanced early termination mechanism based on new attenuation factors

Abstract

This paper proposes two attenuation factors (AF’s) to improve the performance of the soft-output Viterbi algorithm (SOVA) as well as to enhance the early termination mechanism in turbo decoding. The mean square difference between the systematic bipolar coded symbols and the a-posteriori information is used to estimate the first AF. The second AF is computed online for each iteration based on the correlation coefficient between the extrinsic and a-priori information instead of intrinsic information as customary to calculate in literature. The second factor is used in the early termination (ET) scheme which is practically useful to terminate iterations when there is no significant improvement is achieved. In addition, a method for offline computing the AF’s that cover a specific range of signal-to-noise power ratio is provided which results in a reduction of utilization and latency estimates with a shallow degradation in performance. The results show that the proposed scheme outperforms the previous related works by about 0.2 dB at bit error rate (BER) of 10^-5 using interleaver depth of 512 and reducing the average number of iterations (ANI) by about 3 iterations.