Evaluation of Soft Output Decoding for Turbo Codes
Abstract
Evaluation of soft output decoding for turbo codes is presented. Coding theory related to this research is studied, including convolutional encoding and Viterbi decoding. Recursive systematic convolutional (RSC) codes and nonuniform interleavers commonly used in turbo code encoder design are analyzed. Fundamentals such as reliability estimation, log-likelihood algebra, and soft channel outputs for soft output Viterbi algorithm (SOVA) turbo code decoding are examined. The modified Viterbi metric that incorporates a-priori information used for SOVA decoding is derived. A low memory implementation of the SOVA decoder is shown. The iterative SOVA turbo code decoding algorithm is described with illustrative examples. The performance of turbo codes are evaluated through computer simulation. It has been found that the SOVA turbo code decoding algorithm, as described in the literature, did not perform as well as the published results. Modifications to the decoding algorithm are suggested. The simulated turbo code performance results shown after these modifications more closely match with current published research work.
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