Turbo码是一类性能优异的信道编码。它将卷积码和随机交织器相结合，使Turbo码近似随机长码，并采用软输出迭代译码来逼近最大似然译码，获得了接近Shannon理论极限的性能。尤其是Turbo码在低信噪比下的优异性能使其在许多通信系统中都有非常大的应用潜力。在3G和4G移动通信系统中，Turbo码己经成为其信道编码的标准，这极大的促进了Turbo码的研究与应用。 本文在简述Turbo码的编译码原理、对其性能进行分析的基础上，着重研究了Turbo码的译码算法和迭代停止准则。首先，通过仿真研究了分量码、交织长度、迭代次数、编码速率等设计参数对Turbo码误比特率性能的影响，为设计Turbo码提供了参数选择的原则和方法；其次，对MAP和SOVA两类译码算法进行研究，分析比较了不同译码算法的性能和复杂度，并针对传统SOVA性能较差、所需存储空间较大、译码延迟较长等不足，提出了一种SW-MISOVA改进算法。该算法通过引入修正函数对过大的SOVA软输出值进行矫正，使SOVA的性能得到提高，同时运用滑动窗口的思想，降低了存储器数量和译码延迟；最后，分析比较了几种常用的迭代停止准则，并依据交叉熵准则和SOVA算法的原理，给出了一种基于可靠性值的停止准则。经仿真验证，该准则在译码性能几乎没有下降的同时，有效的减少了平均迭代次数，降低了时延。此外，它还进一步降低了计算复杂度和数据存储量，更易于硬件实现。

Turbo codes are a class of high-performance error correction codes in which Convolutional codes and a random interleaver structure are combined to form approximate random long codes. Turbo codes use soft output iterative decoding to approach the maximum likelihood decoding and come closest to approaching the Shannon limit. Turbo codes become very potential for a lot of communication systems because of its excellent performance, especially when they are used within low SNR (signal to Noise Ratio) channels. And they have already been the standard for channel coding in the third and the forth generation mobile communication systems. It promotes the research and application of turbo codes greatly. After an introduction to the coding and decoding principles of Turbo Codes and analysis of their performance, the thesis is dedicated to the research on the decoding algorithm and the iterative stopping criterion. Firstly, the effects of a few design parameters on the BER performance of Turbo codes such as the component coding, the length of the interleaver, the number of iteration and coding rate are simulated and discussed. Accordingly, a basic principle of parameter selection for design of Turbo codes is provided. Secondly, the capacity and complexity of two kinds of decoding algorithm, MAP and SOVA(Soft Output Viterbi Algorithm), are simulated and analysized. There are some defects in traditional SOVA, such as bad performance, high decoding sequence delay and high storage requirement. Aiming to eliminate these defects, a new algorithm named SW-MISOA (Slide-Window Modified Soft-Output Viterbi Algorithm) is presented. On one hand, a correction function is introduced to correct SOVA soft output values exceeding predefined threshold values. As a result, the performance of SOVA is improved. On the other hand, the application of slide windows reduces the effects of decoding sequence delay and storage requirement. Lastly, common stopping criteria of iterative decoding are compared and discussed, then a new stopping criterion is brought up based on reliability following principles of Cross Entropy and SOVA decoding algorithm. The corresponding simulation and analysis shows that the new criterion does help reduce the average number of decoding iteration and the time delay while the BER performance is almost not degraded. Moreover, the complexity of computation and the storage memory is reduced, which is helpful for hardware implementations.