新型卷积码编码器结构与性能分析

综合了LDPC和卷积码的特征,给出了一种卷积码编码器结构的改进方法. 利用此方法可构造稀疏卷积码,进一步基于卷积码编码结构可实现高性能译码. 设计了基于MIMO系统平台的时变新型卷积码结构,并进行仿真分析. 结果表明,应用本文提出的卷积码编码器误码率在10-4时比传统卷积码编码器有2 dB的编码增益提高;同时提出的编码器结构还可实现传统卷积码无法实现的长约束并行编码,具有实现简单、译码延时小的优势. 

Structure and BER of a Novel Convolutional Code

Channel error-correcting coding is essential to improve the communication quality. Low density parity check (LDPC) code with near Shannon limit characteristics has increasing significantcalculation complexity with the increasing code length. A convolutional encoding structure was presented through synthesizing the characteristics of both LDPC and convolutional codes, with which to construct sparse convolutional code and achieve higher decoding performance. Analysis verifies that the presented structure can achieve lower bit error rate under error rate of 10^-4 comparing with traditional convolutional code. Moreover, the simulations based on LTE-A software multi-antenna MIMO platform can realize long constraints and parallel coding, which has advantages of less complexity and small decoding delay.