针对已有Turbo码译码算法延迟长,存储空间需求大的问题,在对算法的计算单元、存储操作进行优化的基础上提出了一种新的状态度量归一化处理方法及基于分块的滑动窗算法,并构建了算法的寄存器传输级模型.该算法将分块并行技术和滑动窗算法有机的结合在一起,能够有效降低运算中的时延及存储资源需求.仿真结果表明,该算法在保证性能的前提下,具有较好的可实现性.
To solve the problem of long time delay and large storage space of the existing turbo decoding,a new state metric re-scaling method and a sliding window algorithm based on sub-blocks are proposed,which is based on the optimization of calculation unit and storage operations,and also we build the register-transmission model for the algorithm.The algorithm combines parallel processing technology and sliding window algorithm organically,effectively reduces the decoding delay and the occupied memory size.The simulation results show that the algorithm has preferable realization without performance degradation.