TURBO CODE RE-ANALYSIS USING DIFFERENT ALGORITHMS

Abstract

Turbo codes are a novel type of forward error correcting codes that have proved to give a perfor- mance close to the channel capacity as proposed by C. Shannon. The parallel concatenation of two identical recursive convolutional encoders that are spaced apart by an interleaver results in a turbo code encoder. The two cascaded decoding blocks used by the turbo code decoder pass along a priori knowledge generated by each block in turn. The decoding approach has the advantage of working iteratively, allowing for an increase in total performance. This study does a performance analysis of turbo codes. The performance study includes two decoding methods: the soft output Viterbi algo- rithm (SOVA), which uses the log-likelihood ratio to produce soft outputs, and the log maximum a posteriori probability (Log-MAP) algorithm. Both punctured and unpunctured codes are studied to determine the impact of utilizing various decoding algorithms. The performance of the two various decoding techniques is then contrasted in terms of bit error rate. MATLAB tools are utilized to per- form simulations.