Detecting Cycles of Length 8 in the Tanner Graph of a QC-LDPC Code Based on Protograph Analysis

2020 ◽  
Vol 56 (2) ◽  
pp. 173-184
Author(s):  
A. V. Kharin ◽  
K. N. Zavertkin ◽  
A. A. Ovinnikov
Keyword(s):  
2020 ◽  
Vol 56 (4) ◽  
pp. 317-331
Author(s):  
A. V. Kharin ◽  
K. N. Zavertkin ◽  
A. A. Ovinnikov
Keyword(s):  

2021 ◽  
Author(s):  
Shyam Saurabh

<p>Structured LDPC codes have been constructed using balanced incomplete block (BIB) designs, resolvable BIB designs, mutually orthogonal Latin rectangles, partial geometries, group divisible designs, resolvable group divisible designs and finite geometries. Here we have constructed LDPC codes from <i>α </i>–<b> </b>resolvable BIB and Group divisible designs. The sub–matrices of incidence matrix of such block design are used as a parity – check matrix of the code which satisfy row – column constraint. Here the girth of the proposed code is at least six and the corresponding LDPC code (or Tanner graph) is free of 4– cycles. </p>


Author(s):  
Jan Broulim ◽  
Vjaceslav Georgiev ◽  
Jan Moldaschl ◽  
Lukas Palocko

2021 ◽  
Author(s):  
Shyam Saurabh

<p>Structured LDPC codes have been constructed using balanced incomplete block (BIB) designs, resolvable BIB designs, mutually orthogonal Latin rectangles, partial geometries, group divisible designs, resolvable group divisible designs and finite geometries. Here we have constructed LDPC codes from <i>α </i>–<b> </b>resolvable BIB and Group divisible designs. The sub–matrices of incidence matrix of such block design are used as a parity – check matrix of the code which satisfy row – column constraint. Here the girth of the proposed code is at least six and the corresponding LDPC code (or Tanner graph) is free of 4– cycles. </p>


2021 ◽  
Vol 4 (9(112)) ◽  
pp. 46-53
Author(s):  
Viktor Durcek ◽  
Michal Kuba ◽  
Milan Dado

This paper investigates the construction of random-structure LDPC (low-density parity-check) codes using Progressive Edge-Growth (PEG) algorithm and two proposed algorithms for removing short cycles (CB1 and CB2 algorithm; CB stands for Cycle Break). Progressive Edge-Growth is an algorithm for computer-based design of random-structure LDPC codes, the role of which is to generate a Tanner graph (a bipartite graph, which represents a parity-check matrix of an error-correcting channel code) with as few short cycles as possible. Short cycles, especially the shortest ones with a length of 4 edges, in Tanner graphs of LDPC codes can degrade the performance of their decoding algorithm, because after certain number of decoding iterations, the information sent through its edges is no longer independent. The main contribution of this paper is the unique approach to the process of removing short cycles in the form of CB2 algorithm, which erases edges from the code's parity-check matrix without decreasing the minimum Hamming distance of the code. The two cycle-removing algorithms can be used to improve the error-correcting performance of PEG-generated (or any other) LDPC codes and achieved results are provided. All these algorithms were used to create a PEG LDPC code which rivals the best-known PEG-generated LDPC code with similar parameters provided by one of the founders of LDPC codes. The methods for generating the mentioned error-correcting codes are described along with simulations which compare the error-correcting performance of the original codes generated by the PEG algorithm, the PEG codes processed by either CB1 or CB2 algorithm and also external PEG code published by one of the founders of LDPC codes


2021 ◽  
Author(s):  
Alireza Hasani ◽  
Lukasz Lopacinski ◽  
Rolf Kraemer

<p>The key computation in the min-sum decoding algorithm of a Low-Density Parity-Check (LDPC) code is finding the first two minima and also the location of the first minimum among a set of messages passed from Variable Nodes (VNs) to Check Nodes (CNs) in a Tanner graph. In this paper, we propose a modified rejection-based scheme for this task which is able to find the one-hot sequence of the minimum location instead of its index. We show that this modification effectively reduces the complexity of min-sum decoding algorithm. Additionally, we reveal a pipelining potential in such a rejection- based architecture which facilitates the multi-frame decoding of LDPC codes and therefore results in improvement in decoding throughput with bearable hardware overhead. Synthesis in an industrial 28nm CMOS technology shows improved results in terms of throughput, power, and chip area.</p>


2021 ◽  
Author(s):  
Alireza Hasani ◽  
Lukasz Lopacinski ◽  
Rolf Kraemer

<p>The key computation in the min-sum decoding algorithm of a Low-Density Parity-Check (LDPC) code is finding the first two minima and also the location of the first minimum among a set of messages passed from Variable Nodes (VNs) to Check Nodes (CNs) in a Tanner graph. In this paper, we propose a modified rejection-based scheme for this task which is able to find the one-hot sequence of the minimum location instead of its index. We show that this modification effectively reduces the complexity of min-sum decoding algorithm. Additionally, we reveal a pipelining potential in such a rejection- based architecture which facilitates the multi-frame decoding of LDPC codes and therefore results in improvement in decoding throughput with bearable hardware overhead. Synthesis in an industrial 28nm CMOS technology shows improved results in terms of throughput, power, and chip area.</p>


2009 ◽  
Vol E92-B (5) ◽  
pp. 1504-1515 ◽  
Author(s):  
Naoto OKUBO ◽  
Nobuhiko MIKI ◽  
Yoshihisa KISHIYAMA ◽  
Kenichi HIGUCHI ◽  
Mamoru SAWAHASHI

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