GRAPHICAL QUANTUM LOW-DENSITY PARITY-CHECK CODES

2012 ◽  
Vol 26 (20) ◽  
pp. 1250118
Author(s):  
YUAN LI ◽  
MANTAO XU ◽  
YINKUO MENG ◽  
YING GUO
Keyword(s):  
Error Correction ◽  
Fast Algorithm ◽  
Ldpc Codes ◽  
Quantum Codes ◽  
Error Correction Codes ◽  
Low Density ◽  
Parity Check ◽  
Graphical Approach ◽  
Low Density Parity Check ◽  
Parity Check Codes

Graphical approach provides a direct way to construct error correction codes. Motivated by its good properties, associating low-density parity-check (LDPC) codes, in this paper we present families of graphical quantum LDPC codes which contain no girth of four. Because of the fast algorithm of constructing for graphical codes, the proposed quantum codes have lower encoding complexity.

Performance of IEEE 802.11n LDPC codes

2017 ◽  
Vol 11 (22) ◽  
pp. 1065-1073
Author(s):  
Yenny Alexandra Avendano Martinez ◽  
Octavio Jose Salcedo Parra ◽  
Giovanny Mauricio Tarazona Bermudez
Keyword(s):  
Error Detection ◽  
High Performance ◽  
Ldpc Codes ◽  
Low Density ◽  
Parity Check ◽  
Ieee 802.11N ◽  
Noise Environment ◽  
Low Density Parity Check ◽  
Parity Check Codes

LDPC (Low Density Parity Check Codes) is a set of algorithms that send, receive and correct in a noise environment, frames transmitted in a LAN environment. This article demonstrates the high performance of the LDPC in environments of noise, compared to the CRC error detection code highly currently implemented, in this way the efficiency of LDPC is shown specifically over the 802. 11n protocol.

EFFICIENT RECOVERY TECHNIQUE FOR LOW-DENSITY PARITY-CHECK CODES USING REDUCED-SET DECODING

2008 ◽  
Vol 17 (02) ◽  
pp. 333-351 ◽  
Author(s):  
K. M. S. SOYJAUDAH ◽  
P. C. CATHERINE
Keyword(s):  
Ldpc Codes ◽  
Low Density ◽  
Parity Check ◽  
Coding Gain ◽  
Inference Procedure ◽  
Recovery Algorithm ◽  
Low Density Parity Check ◽  
Recovery Technique ◽  
Efficient Recovery ◽  
Parity Check Codes

We introduce a recovery algorithm for low-density parity-check codes that provides substantial coding gain over the conventional method. Concisely, it consists of an inference procedure based on successive decoding rounds using different subsets of bit nodes from the bipartite graph representing the code. The technique also sheds light on certain characteristics of the sum–product algorithm and effectively copes with the problems of trapping sets, cycles, and other anomalies that adversely affect the performance LDPC codes.

Modified Bit-Flipping Decoding of Low-Density Parity-Check Codes

2013 ◽  
Vol 710 ◽  
pp. 723-726
Author(s):  
Yuan Hua Liu ◽  
Mei Ling Zhang
Keyword(s):  
High Throughput ◽  
Error Probability ◽  
Ldpc Codes ◽  
Low Complexity ◽  
Low Density ◽  
Parity Check ◽  
Excellent Performance ◽  
Low Density Parity Check ◽  
Lower Complexity ◽  
Parity Check Codes

A novel bit-flipping (BF) algorithm with low complexity for high-throughput decoding of low-density parity-check (LDPC) codes is presented. At each iteration, a novel threshold pattern is used to determine the code bits whether to be flipped or not, and the flipping error probability is effectively decreased. Compared with the weighted BF algorithm and its modifications, the modified BF algorithm has significantly lower complexity and decoding time. Through simulations the proposed BF algorithm is shown to achieve excellent performance and fast convergence speed while maintaining significantly low complexity thus facilitating high-throughput decoding.

Intensity Reflection Coefficient Based Min-Sum Decoding for Low Density Parity Check Codes

Frequenz ◽  
2012 ◽  
Vol 66 (7-8) ◽  
Author(s):  
Mohammad Rakibul Islam ◽  
Khandaker Sultan Mahmood ◽  
Md. Farhan Tasnim Oshim ◽  
Md. Moshiur Rahman Farazi
Keyword(s):  
Reflection Coefficient ◽  
Ldpc Codes ◽  
Superior Performance ◽  
Low Density ◽  
Parity Check ◽  
Factor Intensity ◽  
Concatenated Coding ◽  
Low Density Parity Check ◽  
Parity Check Codes ◽  
Intensity Reflection

AbstractLow Density Parity Check Codes (LDPC) give groundbreaking performance which is known to approach Shannon’s limits for sufficiently large block length. Historically and recently, LDPC have been known to give superior performance than concatenated coding. In the following paper, a proposal to modify the standard Min-Sum (MS) algorithm for decoding LDPC codes is presented. This is done by introduction of a factor, intensity reflection coefficient (IRC),

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