论文部分内容阅读
借助无噪条件下的压缩感知理论,研究了BCH码的译码方法。采用校验矩阵H作为测量矩阵,伴随式S作为测量信号,建立了重构差错图案E的压缩感知模型,采用基追踪BP算法,重构了BCH码的差错图案E。以(15,11)BCH码为例,验证了重构的差错图案E是正确的。根据收码R和差错图案E计算出码字C估值。通过误码率和码字C估值成功率,比较了基追踪BP算法和Berlekamp迭代译码算法的译码效果。以BCH短码和长码为例,进行仿真实验,验证了采用压缩感知理论和基追踪BP算法实现BCH码译码是可行和有效的。
With the theory of compressed sensing under noiseless conditions, the decoding method of BCH codes is studied. Using the parity check matrix H as the measurement matrix and S as the measurement signal, a compressed sensing model of the reconstructed error pattern E is established. The error tracking pattern B of the BCH code is reconstructed by using the base pursuit BP algorithm. Taking the (15,11) BCH code as an example, it is verified that the reconstructed error pattern E is correct. The estimate of the codeword C is calculated from the received code R and the error pattern E. Through the error rate and the success rate of the C code estimation, the decoding performance of the base pursuit BP algorithm and Berlekamp iterative decoding algorithm is compared. Taking BCH short code and long code as an example, simulation experiments are carried out to verify that it is feasible and effective to compress BCH codes using compressed sensing theory and back-tracking BP algorithm.