Adaptive Algorithm for Turbo Decoding Based on Logarithmic Cross Entropy

Considering the relationship between the extrinsic information of the decoder and the signal-to-noise ratio, we propose a blind estimation algorithm based on logarithmic cross entropy. And then, the performance of the algorithm is analyzed. From the deduction, it is concluded that the estimated SNR is credible for its extremely low fault probability. At last, the blind estimated SNR is exploited to make stop criterion, and it contributes to decoding adaptively. The simulation results show that the proposed adaptive decoding algorithm based on the blind estimated SNR can greatly decrease the complexity of the channel estimator with little degradation of the performance and reduction of decoding delay