基于压缩感知理论的线性分组码译码

Decoding of Linear Block Code Based on Compressive Sensing Theory

将压缩感知理论应用于线性分组码的译码,提出差错图案E重构的压缩感知模型及校验矩阵H作为测量矩阵的构成形式和性质.将伴随式S作为测量信号,校验矩阵H作为测量矩阵,以(15,7)循环码为例,采用基追踪(BP)算法重构差错图案E的估值,并设计线性分组码译码的仿真实验方案.仿真实验结果表明,采用压缩感知理论与BP算法能较好完成线性分组码的译码.

Applying the compressive sensing theory to the decoding of the linear block code,we proposed the compressive sensing model of the reconstructing the error pattern E,the check matrix H as the form and properties of the measurement matrix.The syndrome S was used as the measurement signal,the check matrix H was used as the measurement matrix,and the cyclic code（15,7）was used as the example to reconstruct the estimation of the error pattern E by using the basis pursuit（BP）algorithm.The simulation experiment scheme of the decoding of the linear block code was designed.The simulation experiment results show that the linear block codes can be decoded well by the compressive sensing theory and the BP algorithm.