An efficient tail-biting MAP decoder for convolutional turbo codes in OFDM systems

In this paper, we consider an efficient tail-biting MAP (Maximum a posteriori probability) decoding algorithm for CTC (Convolutional Turbo Codes) specified in IEEE 802.16a/e OFDM. For short block lengths, the CTC encoder uses tail-biting scheme instead of inserting tail bits for path termination. To process a tail-biting codeword, the decoder begins with estimating the circulation states. But this estimation procedure increases the computational complexity. We first describe the CTC decoding process based on the MAP algorithm of the nonbinary codes. Using a suboptimal iterative decoding method, we propose an efficient circulation states estimation algorithm. The BER (Bit Error Rate) performance of the proposed algorithm is evaluated using computer simulations. The results show that the proposed algorithm performs close to the ideal case with known circulation states information.