Attenuation Factor approach to minimize the correlation effect in Soft Output Viterbi Algorithm

Abstract

Prominent turbo decoding algorithms used for wireless applications are Maximum A posteriori Probability (MAP) and Soft Output Viterbi Algorithm (SOVA). These algorithms are known for their error correcting performance close to Shannon’s limit. MAP algorithm is intense in terms of computational complexity but gives optimal performance. SOVA algorithm gives sub-optimal performance with reduced complexity and is appropriate for real time implementation. Sub-optimal performance of SOVA is attributed to correlation effect that exists between intrinsic and extrinsic information exchanged between component turbo decoders. This paper aims at reducing the correlation effect in SOVA using Attenuation Factor (AF) approach. In this approach, two AF values are selected through MATLAB simulation that minimizes the correlation between intrinsic and extrinsic information of the two constituent decoders. Acquired AF values are analysed in Additive White Gaussian Noise (AWGN) and Rayleigh fading channel. To justify the efficiency of the proposed SOVA algorithm, EXIT chart analysis, BER analysis and complexity analysis are done. The results depict that the proposed AF approach reduces the correlation effect in SOVA with nominal BER and complexity.