LDPC decoding method based on hierarchical minimum sum algorithm

Abstract

The invention provides an LDPC decoding method based on a hierarchical minimum sum algorithm. This method divides the check matrix of LDPC into several check nodes according to the rows, divided intovariable nodes by column, and when the element of the parity matrix of the LDPC is 1, it is assumed that the check node corresponding to the row in which the element is located and the variable node corresponding to the column in which the element is located have connections. The method is characterized in that when the number of iterations does not reach a predetermined maximum number of iterations or the LDPC checksum is not a total zero vector, the following steps are repeatedly executed: the variable node updates the information transmitted to the connected check node according to the weighted average of the received two external information values. The checking node updates the information transmitted to the connected variable node according to the weighted average value of the received two external information values. The posterior probability of the variable node is used for decoding decision. The decoding method of the invention can improve the decoding performance and is easyto realiz by hardware.

Description

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AI Technical Summary

Benefits of technology

The present in this patented technology improves error correction codes by adding weights that can be adjusted based upon factors like data size or frequency content (the number of times it has been repeated). This helps prevent errors from happening during transmission over communication channels such as wireless networks. Additionally, there are also improvements made for Layer 3 protocols which use different types of messages called message blocks instead of plaintext. These modifications help reduce interference between signals sent through these systems while still maintaining their effectiveness at transmitting them correctly. Overall, this innovative technique enhances error detection capabilities without making complex calculations more difficult than previous methods.

Problems solved by technology

Technological Problem: Current methods for deciding whether certain bits should be added during data processing involve complicated computations involving multiplication and division operators. These techniques require significant computational resources due their efficiency compared to simpler ones like binary search tree codes.

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