5bit quantization method applied to LDPC decoding

Abstract

The invention provides a 5bit quantization method applied to LDPC decoding, and relates to a decoder for a communication channel. The method comprises the following steps of: based on an MS-offset algorithm, designing an information quantization expression method in a decoding process of an LDPC decoder, wherein the information quantization expression method is a corresponding conversion method mainly applied between a 5bit non-uniform quantization value and a 6bit uniform quantization value; and performing hardware design corresponding to the conversion method, thus ensuring that quantization decoding performance nearly in accordance with floating point decoding can be realized with few quantization bit number. Because the 5bit non-uniform quantization value is transmitted between a variable point calculation unit and a checkpoint calculation unit, the wiring complexity and the information memory overhead are reduced; and in the variable point calculation unit, the 5bit non-uniform quantization value is converted into the 6bit uniform quantization value and then operation is performed so as to enlarge the expression range of the quantization information and improve the decoding performance.

Description

technical field [0001] The invention relates to a decoder of a communication channel, in particular to a 5-bit quantization method mainly aimed at LDPC low-density parity check codes and applied to LDPC decoding. Background technique [0002] In 1962, Gallager (R.G.Gallager.Low-Density Parity-Check Codes.IRE Transon.Inform.Theory.1962, (8): 21-28) first proposed the low-density parity-check code (LDPC code), LDPC code allows A high degree of parallel operation is suitable for high data rate throughput applications, such as broadband wireless multimedia communication and magnetic storage systems, but due to the complexity of its decoding algorithm, it has not received enough attention. Among these decoding algorithms, the performance of the BP sum-product algorithm is better, but the sum-product algorithm based on the log-likelihood ratio information uses the hyperbolic tangent function as the core calculation, and the complexity is quite high when implemented in hardware. T...

AI Technical Summary

Problems solved by technology

Generally speaking, in the LDPC decoding process, when using less quantization bits, such as 5-bit or 6-bit quantization information representation method, quantization decoding will have a decoding performance loss of 0.1-0.2dB compared with floating-point decoding

[0019] Generally speaking, the more quantized bits of information, the better the decoding performance, but the hardware resource overhead will increase, and the fewer quantized bits will reduce the hardware resource overhead. However, compared with floating-point decoding, the quantized decoding performance will change. much worse

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