Research On Parallel Interleaver And Algorithm Of Turbo Coding

With the performance closing to Shannon limit, Turbo coding has received widely attention in many fields, such as wireless communication, since it was proposed in1993. Turbo coding has been adopted as one of the channel coding scheme by3G and4G communication systems. With the rapid development of communication technology, a large number of data need to be dealt with. For example, in LTE system, the data rate in uplink is50Mbps, in downlink that is100Mbps. Therefore, how to fulfil the requirement of high rate decoding is the main point of Turbo coding research.General Purpose Processer (GPP) has the strong ability in data processing, rich storing resource and is easy to develop and maintain. With all those advantages, it has been widely used in many fields. GPP has been used in wireless communication which has been dominated by DSP and FPGA for a long time. GPP supports parallel signal processing with its own structure and SIMD technology. Therefore, it can improve the effciency of signal processing. In this paper we design a kind of Turbo parallel decoder based on Scale-Max-Log-MAP, taking advantage of the structure of GPP and SIMD technology.One difficulty in Turbo parallel decoder designing is the design of parallel interleaver. Because every subdecoder may visit the same interleaver in the same time, when designing interleaver, we should avoid visiting interrupt. That means the design of interleaver could avoid the visit of same address by all subdecoder at the same time.The QPP interleaver structure and mapping rule is described in this paper in detail. The paper also shows the computing process of the address.The paper firstly analyses the structure of Turbo encoding and described the component coder and the process of encoding in detail. Next, the structure of Turbo decoder and decoding process is introduced. As the core of MAP algorithm, the introduction of BCJR is necessary. In the foundation of BCJR, MAP algorithm and Log-MAP algorithm is introduced. After that, the improvement of MAP algorithm and Log-MAP algorithm is analysed, which include linear MAP algorithm, MAX-Log-MAP algorithm, Log-MAP based on chart, and Scale-Max-Log-MAP. The result of simulink shows that when considering complexity and performance, Scale-Max-Log-MAP is the best choice.