Parallel Decoding Structure of Turbo Code Based on Double Prediction Control

Abstract

Iterative decoding structure is the main feature of Turbo code decoding. It can improve the performance of Turbo decoding, but also increase the decoding complexity, time delay and power consumption. This paper proposes a parallel decoding structure of Turbo code based on double prediction control, i.e., using double prediction control module instead of two iterative decoding algorithms. Since the computation quantity and computing time of the Double Prediction Control Algorithm (DPCA) is smaller than the traditional decoding algorithm, the complexity and delay of the decoding algorithm can be reduced by the new decoding scheme presented in this paper. Exterior information simulations show that comparing to the traditional iterative decoding, time delay can be reduced by at least three times by using prediction scheme each time, while the BER performance simulation results show that the error-rate performance of the new decoding structure based on DPCA is only lower by 0.1 dB than the traditional Turbo decoding structure, but has a good approximation BER curves to the traditional one. When reasonably choose the two prediction intervals, it can achieve the coincident BER curve.