Improved SOVA and APP decoding algorithms for serial concatenated codes

Abstract

We propose a simple remedy for the exaggerated extrinsic information produced by the soft-output Viterbi algorithm (SOVA). We argue that what leads to these optimistic extrinsic values is the inherent strong correlation between the intrinsic information (input to the SOVA) and extrinsic information (output of the SOVA). The proposed remedy involves employing two attenuators, one applied to the immediate output of the SOVA and another applied to the extrinsic information before it is passed to the other decoder (assuming iterative decoding). We examine the modified SOVA (MSOVA) on additive white Gaussian noise (AWGN) and fading channels for serial concatenated codes (SCCs). We show that the MSOVA provides substantial performance improvements over both channels. For example, it provides improvements of about 0.8 to 1.0 dB at P/sub b/ = 10/sup -5/ in AWGN, and about 1.4 to 2.0 dB at P/sub b/ = 10/sup -5/ in fading channels, all relative to the SOVA. We extend the proposed modifications to the a posteriori probability (APP) algorithm with favorable results. We demonstrate that the modified APP (MAPP) provides performance improvements between 0.3 to 0.6 dB at P/sub b/ = 10/sup -5/ relative to the APP.