Decoding method of low density parity check codes

Abstract

The invention relates to a decoding method of low density parity check codes, which comprises the main steps as follows: obtaining check node information by using simplified variable nodes during the primary data iteration decoding, and storing primary information of received data; transmitting same information to different check nodes following each variable node, and storing necessary group information; calculating the information of the check nods to the variable nodes by utilizing the stored group information, at last performing the trial and error decoding and judging whether iteration is finished or not, and continuously performing the trial and error decoding if the iteration is always needed. The invention leads the check node part to only need to store M groups of data through improving the check node storage scheme and the variable node calculation mode, thereby obviously lowering the data storage capacity required by decoding and the complexity of data exchange between the variable nodes and the check nods.

Description

technical field [0001] The invention relates to a parity-check code decoding method, which is a low-density parity-check code decoding method based on a minimum sum algorithm, and belongs to the technical field of electronic communication. Background technique [0002] In modern communication systems, the noise and fading in the channel will cause errors in the transmitted binary data. In order to ensure the reliable transmission of information, it is necessary to use error correction coding technology. Low-density parity-check (LDPC) codes have attracted much attention because of their excellent performance, and are widely considered to be promising error-correcting coding schemes. [0003] The LDPC code can be defined by a parity check matrix H whose size is M×N, where N represents the coded bit length, M represents the parity bit length, and the number of non-zero values ​​in each row and column of the matrix H is defined as row weight and column weight. [0004] The Lo...

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Problems solved by technology

[0016] It can be seen that a large amount of intermediate data needs to be stored in the calculation process of the MS algorithm, and a large amount of data exchange between variable nodes and check nodes will lead to a complex interconnection network. These shortcomings make the design and implementation of the decoder very complicated.

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