The Research On Blind Identification Of The Parameters Of LDPC Codes And The Restoration Of The Parity Check Matrix

In digital communication,in order to ensure the reliability of communication,the transmitter and receiver usually uses channel coding technology to add redundancy to protect information.The identification technology of channel coding under unknown circumstances is to identify and estimate the parameters of channel coding under the condition of third party reception.It has a wide range of applications in non-cooperative communication and intelligent communication area.In this thesis,the blind identification of LDPC code parameters and the restoration of its sparse check matrix are studied.The main contents of the study are as follows:1.This thesis proposes an algorithm to estimate the quasi-cyclic block size of QCLDPC by using code bits under blind reception.Firstly,the thesis discusses the code structure and analyzes the characteristics of its sparse check matrix.By using the check vector’s shifting character,the algorithm can identify the length of the QC block.Simulation experiments show that the algorithm has good practicability in the case of the error rate to 1.0e-3.This thesis discusses the algorithm of estimating the code length and code rate of LDPC code by defining the consistency of the code.Simulation experiments show that algorithm can effectively identify code length and code rate of different kinds of LDPC code in the case of the error rate to 2.0e-2.2.This thesis improves a blind recovery algorithm for sparse check matrix of LDPC code.This thesis using the idea of iterative decoding,sets a more efficient decision condition of sparse vector,improves the threshold value of algorithm iteration,and comprehensively uses the weight characteristics of LDPC sparse check matrix to filter the search results,which can obtain the sparse check vector of LDPC code under higher error rate conditions.The optimized and improved algorithm continuously uses the currently obtained sparse check vector set to decode and correct the data,so as to reduce the error rate of the data;The simulation results show that the algorithm can successfully recover the sparse check matrix of(23041152)LDPC codes with error bit rate at 2.0e-3.3.This thesis designs a sparse check matrix recovery algorithm for QC-LDPC codes based on code space compression method.The algorithm makes use of the cyclic shift feature of the check vectors of QC-LDPC code,and realizes the "dimension reduction" of the check vectors by "block compression" of the code word space vector,which can greatly reduce the amount of computation required to obtain the check vectors in high error rate condition.Through theoretical analysis and simulation experiments,this thesis proves that the algorithm can successfully recover the sparse check matrix of LDPC codes which code length is 2304,when the bit error rate reaches to 3.0e-3;compared with the traditional algorithm,it can successfully reconstruct its sparse check matrix under higher error rate.