A low complexity channel estimation algorithm and architecture design in turbo codes with early termination techniques

One requirement of iterative maximum a posteriori probability algorithm (MAP) decoding of turbo codes is the knowledge of the channel SNR. The correction ability of turbo decoding is degraded by the mismatch of channel SNR. In this paper, a low complexity channel estimation algorithm based on early termination techniques, which is used to reduce the number of iterations, is proposed. Both of the hard and soft decisions for early termination techniques are simulated with the SNR mismatch. Our algorithm takes the advantages of reducing the iterations and easy implementation on channel estimation. Only 3 iterations can be achieved compared with the analyzed 20 iterations at 2-dB true SNR. Based on our simulation results, the proposed method can practically estimate the reliable channel SNR to refine the correction performance after several frames, and get 0.1-dB coding gain loses as compared to true channel SNR at BER = 10^-5.