Low-complexity multivariate LDPC code decoding method and decoder

Abstract

The invention discloses a low-complexity multivariate LDPC code decoding method, which comprises the steps of 1, initializing; 2, detecting signals; 3, judging whether the number of cycles reaches the preset maximum number of cycles or not, executing a step 4 if the number of cycles does not reach the preset maximum number of cycles, and otherwise, executing a step 5; calculating the checksum of a most likely estimation symbol sequence by a decoding stop module, executing the step 5 if the checksum is an all-zero vector, and otherwise, executing a step 6; 5, outputting a decoding result; 6, carrying out updating on information transmitted to check nodes by a variable node; 7, carrying out information updating by each check node; 8, carrying out updating on information transmitted to a detection node by the variable node; and 9, carrying out information updating by the detection node. The invention further discloses a low-complexity multivariate LDPC decoder. The method disclosed by the invention is simple in step, capable of meeting the requirements of high speed and high efficiency, capable of acquiring better decoding performance and wider application conditions, high in practicability, good in use effect and convenient for popularization and application.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a low-complexity multivariate LDPC code decoding method and a decoder. Background technique [0002] With the rise of sparse graph codes and iterative decoding algorithms at the end of last century, low-density parity check codes (LDPC codes) have been widely studied and applied. At the same time, multivariate LDPC codes based on high-order finite field GF(q) (q>2) have advantages over binary LDPC codes in short and medium code lengths, especially when combined with high-order modulation. Extensive research in academia. However, the relatively high decoding complexity of multivariate LDPC codes weakens its advantages in performance. [0003] In order to reduce the complexity of the decoding algorithm, Davey et al. proposed the QSPA (FFT-QSPA) algorithm based on Fast Fourier Transform (FFT), which reduces the complexity of the original QSPA algorithm. Later...

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Problems solved by technology

However, when these soft-decision decoding algorithms decode multi-element codes, especially when q is very large, their complexity is still too high for a practical multi-element LDPC coded modulation system, so that it is difficult to realize

[0004] Decoding algorithms based on reliable metrics are another effective decoding algorithm for multi-ary codes. This type of algorithm has achieved a good compromise between performance and decoding complexity, but most of the decoding algorithms based on reliable metrics Only applicable to second-order modulation, not applicable to multivariate LDPC coded modulation system

For multivariate LDPC coded modulation systems, Wang Xuepeng and Bai Baoming proposed a joint iterative detection-decoding (IJDD) algorithm based on reliable metrics. Although the algorithm has extremely low complexity, it loses certain performance compared to the QSPA algorithm, and the algorithm It is only suitable for multi-codes with high column weights, and it is not suitable for decoding multi-codes with low column weights

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