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Method for designing LDPCA codes in asymmetric structure distributed source coding system

A distributed source, asymmetric structure technology, applied in the field of source coding, can solve the problem of no rate adaptation and so on

Active Publication Date: 2014-06-25
HARBIN INST OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Therefore, only a small fraction of compression ratios without rate adaptation approach the Slepian-Wolf bound

Method used

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  • Method for designing LDPCA codes in asymmetric structure distributed source coding system
  • Method for designing LDPCA codes in asymmetric structure distributed source coding system
  • Method for designing LDPCA codes in asymmetric structure distributed source coding system

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Embodiment 1

[0065] The channel in this embodiment adopts BSC channel, pCrossover is from 0 to 0.5; the code length is designed to be 6336; the variable node degree of the regular code is 3; the degree distribution characteristics of the irregular code are given in the corresponding table below. This part simulates the performance of LDPCA under different code lengths, degree distributions, and different statistical conditions between source and side information. All LDPC bipartite graph construction methods used here: first construct the bipartite graph with the highest compression rate, and other The factor graph is obtained by consecutively partitioning the syndrome nodes into pairs. It is assumed that the decoder can fully detect the distortion-free recovery of the source. The simulation results also show that under the premise that the received codeword is generated independently of the function that generates the source, if the received cumulative syndrome has the same length as the ...

Embodiment 2

[0079] Embodiment 2: Under the condition of asymmetric structured distributed source coding, we simulated the LDPCA coding method. The non-regular traditional LDPCA with variable node degree distribution from 2 to 21 is the most comparable. In the simulation results, the code length n is set to 6336. The number L of different compression ratios of the LDPCA code is 66, and the compression ratios range from 65 / 66 to 0. Therefore, each step of compression transmits 96 symbols. In the proposed method, the compression rate from 1 / L to k / L still adopts the original LDPCA code, and the compression rate from (k+1) / L to 1 adopts the proposed method. After removing the maximum degree of variable nodes, the redesigned optimal degree distribution characteristics are as follows:

[0080] λ(x)=0.3264x+0.4254x 2 +0.1384x 6 +0.0794x 7 +0.0304x 18 (6)

[0081] In all simulations, the decoding side adopts the BP decoding method, and the maximum number of iterations is 100.

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Abstract

The invention provides a method for designing LDPCA codes in an asymmetric structure distributed source coding system and relates to the technical field of source coding. Traditional LDPCA codes are still adopted for the compression rate ranging from 1 / L to k / L, and the provided method is adopted for the compression rate ranging from (K+1) / L to 1. After the maximum degree of variable nodes is removed, a distribution character of redesigned optimum degree is as follows: lambda(x) = 0.3264x + 0.4254x2 + 0.1384x6 + 0.0794x7 + 0.0304x18. A belief propagation decoding method is adopted at the decoding end, and the maximum iteration number s 100. The difference of the method and a claude elwood Shannon can be still kept small in a high-speed region, and the LDPCA codes are greatly better than the traditional LDPCA codes. Good effect is obtained in a speed region Rx<[47 / 66,1] by adopting the method and approaches a Selpian-Wolf boundary, and the defect that the traditional LDPCA codes are only designed for the fixed speed is overcome. The method is characterized by selecting a maximum number of variable nodes and adopting high-compression-ratio optimum degree distribution design.

Description

technical field [0001] The invention relates to an LDPCA code design method in an asymmetric structure distributed information source coding system, and relates to the technical field of information source coding. Background technique [0002] Asymmetric distributed source coding such as figure 1 shown. Source X can be transmitted losslessly with a small number of bits, while side information Y (related information about X) is only known at the decoding end. In this way, the information source X needs to be compressed without knowing the side information Y, and the information source X is restored through the side information Y at the decoding end. Slepian and Wolf proposed in 1973 that lossless compression can be achieved when the rate R≥H(X|Y), where H(X|Y) is the conditional entropy, and X and Y are discrete. It can be obtained that this rate field is consistent with the case where the side information Y is known at the encoder. Wyner and Ziv further extended this res...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L1/00
Inventor 于启月王柏岩孟维晓
Owner HARBIN INST OF TECH
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