LDPC decoder for decoding a low-density parity check (LDPC) codewords

Abstract

As a result of transmitting a low-density parity-check (LDPC) codeword (b) having a number (N) of codeword bits consisting of K information bits and N parity bits, for the received An LDPC decoder for decoding a codeword (Y), comprising: a memory for receiving codeword bits of a noisy codeword (Y), storing the codeword bits from the received noisy codeword (Y) and from The a priori estimate (Qv) of the predetermined value of the predetermined parameter of the communication channel; the generalized check node processing unit, iteratively calculates the messages on the edge of the bipartite graph according to the serial scheduling, and in each iteration, the check for the bipartite graph Node (C), all adjacent variable nodes (V) connected to the check node (C), calculate the input message (Qvc) from the adjacent variable node (V) to the check node (C) and from Output message (RCV) from a check node (C) to a neighboring variable node (V).

Description

technical field [0001] The present invention relates to the field of data communication, in particular, to redundant coding for error correction and error detection. Background technique [0002] Low-density parity-check codes (LDPC) are a class of linear block codes that provide near capacity performance for larger sets of data transmission and storage channels, while allowing achievable encoding and decoding strategies. LDPC codes were first proposed by Gallager in his doctoral dissertation in 1960 (R. Gallager: "Low-density parity check codes", IRE Transformation Series pp. 21-28, January 1962). From a practical point of view, the most notable feature of Gallager's work is the citation of an iterative decoding algorithm, for which he has shown that, when applied to sparse parity-check matrices, it is possible to A significant portion of the channel capacity is achieved. [0003] LDPC codes are defined using a sparse parity check matrix comprising a small number of non-z...

AI Technical Summary

Problems solved by technology

The performance of LDPC decoders according to the state of the art suffers when the number of decoding iterations defined by the threshold is limited

[0068] Traditional LDPC decoding methods and such as Image 6 Another drawback of the corresponding LDPC decoder shown is that checking that the decoding is converged requires a separate convergence test block to perform the convergence test

[0069] Traditional LDPC decoding methods using overflow scheduling and such as Image 6 Another drawback of the corresponding LDPC decoder shown is that the required memory size is relatively high

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