Quasi-cyclic low-density parity-check code decoder and decoding method

Abstract

The invention discloses a quasi-cyclic low-density parity-check code decoder which comprises an initializing unit used for receiving the log-likelihood ratio of code word information from a communication channel, a decoding unit used for calculating the update information between a close-by variable node and a check node according to a message transmission rule, a decoding convergence judging unit used for judging the finish of decoding according to the convergence of the update information of the variable node after each iteration or whether the maximum predetermined iteration time is reached, and a hard decision unit used for implementing hard decision according to the symbol of the variable code information after decoding and obtaining code words. The invention also discloses a decoding method of a quasi-cyclic low-density parity-check code which comprises the steps of initializing each non-zero position in a check matrix H, iterative process, and trying to judge. The invention can accelerate the convergence rate of decoding, reduce the performance loss caused by quantification and lower the complexity of realization of the decoder.

Description

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AI Technical Summary

Benefits of technology

This technology uses both parallel schedule mechanisms for improving decode efficiency while minimizing energy usage on circuits. It also includes algorithms called delta function based algorithm(DFA). These techniques help reduce delays when updating data from previous stages during processing. Additionally, it simplifies the process of checking nodes by utilising different levels of error detection rather than just relying solely upon binary values like 0's/1'. Overall these technical improvements improve overall system performance and decrease its cost per bit compared to existing methods such as scalar coding.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the efficiency or reliance of binary coding over other types of convolutional codes such as ReLU X transform coefficients and Long Block Grass Belief Desorption Algorithm (LCBDA). While certain techniques can be applied to these matrices, including randomized versions thereof, there has been limited successes due to their limitations.

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