Method for generating LDPC (Low Density Parity Check) code check matrix, and LDPC code coding method

Abstract

The invention discloses a method for generating an LDPC (Low Density Parity Check) code check matrix and an LDPC code coding method based on the LDPC code check matrix. The method for generating the LDPC code check matrix comprises the following steps of firstly establishing an index matrix, then establishing a check matrix by the indexing matrix, and specifically, generating the check matrix after expanding each number axy in the index matrix A into a q order (0, 1) matrix; and enabling elements in the positions (i, iaxy (modq+1)) to be 1, enabling elements in other positions to be 0, wherein i = 1, 2, 3 ellipsis q. In addition, the check matrix being a combination of a matrix which is generated by adopting the method and a double-diagonal matrix is provided. The invention also provides the LDPC code coding method by adopting the check matrix generated by any optional method. The method for generating the LDPC code check matrix and the LDPC code coding method have the advantages of easiness in design, low coding complexity, small storage space and excellent performance.

Description

technical field [0001] The invention relates to the field of digital communication research, in particular to a method for generating an LDPC code check matrix and an LDPC code encoding method based on the matrix. Background technique [0002] In 1962, Gallager proposed binary regular LDPC codes in his doctoral dissertation, also known as Gallager codes. Gallager proved that this kind of code has good Hamming distance characteristics, and it is a progressive good code that meets the GV limit. However, due to the limited computing power at that time, LDPC codes were not considered practical codes, and they did not receive people's attention for a long time . Until 1996, MacKay and Neal first revealed and proved that LDPC codes had the performance of approaching the Shannon limit by using BP iterative decoding algorithm. Since then, the research on LDPC codes has entered a new stage. [0003] Compared with Turbo codes, LDPC codes have a set of more systematic optimization de...

AI Technical Summary

Problems solved by technology

The randomization method is a commonly used LDPC code encoding method. This method has good performance, but it is usually not conducive to hardware implementation. The most commonly used method is the pi rotation method.

The pi rotation method introduces a double-diagonal structure, which enables simple iterative encoding, and the encoding calculation complexity is relatively low, which can reduce the requirements for the main frequency of the processing chip to reduce power consumption, but its disadvantage is that it needs to store a very large The matrix consumes a lot of storage resources and brings other costs up. For some low-power applications, it is necessary to reduce the main frequency of the processing chip and do not want to increase the storage space. The direct use of the pi rotation method will be limited.

Images