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International Journal of Business Intelligents

An Efficient Majority Error Detection in Logic Decoding with Euclidean Geometry Low Density Parity Check (Eg-Ldpc) Codes

M .Vengadapathiraj Mr, U. Maheswaran, A.Karunakaran Mr

Published Jun 11, 2019• 0 citations
Publisher

Abstract

In a recent article, a technique was proposed to step up the majority logic decoding of variation set low density parity check codes. This is helpful as majority logic decoding can be implemented serially with trouble-free hardware but requires a huge decoding time. The method detect whether a word has errors in the initial iterations of majority logic decoding, and at what time there are no errors the decoding split ends without completing the rest of the iterations. While the majority words in a memory will be error-free, the average decoding time is significantly reduced. The outcome obtained proves that the technique is also effective for EG-LDPC codes. General simulation results are given to precisely estimate the prospect of error detection for different code sizes and numbers of errors.

DOI
10.20894/ijbi.105.008.001.003

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In a recent article, a technique was proposed to step up the majority logic decoding of variation set low density parity check codes. This is helpful as majority logic decoding can be implemented serially with trouble-free hardware but requires a huge decoding time. The method detect whether a word has errors in the initial iterations of majority logic decoding, and at what time there are no errors the decoding split ends without completing the rest of the iterations. While the majority words in a memory will be error-free, the average decoding time is significantly reduced. The outcome obtained proves that the technique is also effective for EG-LDPC codes. General simulation results are given to precisely estimate the prospect of error detection for different code sizes and numbers of errors.
A reliability-based iterative majority-logic decoding algorithm for regular low-density parity-check (LDPC) codes was recently proposed by Huang et al. In this paper we present an improved version of that algorithm by introducing a different reliability measure for each check-sum of the parity-check matrix, and taking it into account in the computation of the extrinsic information that is used to update the reliability measure of each received bit in each iteration. Some simulations results are given, which show that the new algorithm, while requiring very little additional computational complexity, not only achieves a considerable error performance gain over the standard one, but also, importantly, outperforms the iterative decoding based on belief propagation (IDBP), especially for short and medium block length finite-geometry (FG) LDPC codes.
Hard decision decoding of low density parity check (LDPC) codes has potential applications in practical settings like data storage. For this purpose, it is important for the code to have an assured minimum distance and, hence, guaranteed error correction capability. In this paper, we show that with very high probability the guaranteed error correction capability of Euclidean geometry (EG) codes using threshold-optimized, iterative majority logic (ML) decoding is much greater than the usual single iteration ML decoding, making these codes much more attractive for hard decision decoding. For instance, the (262143, 242461, t/spl ges/256) EG code (a (512, 512)-regular LDPC code) can correct t=580 bit errors with probability better than 1-1/spl times/10/sup -58/.
This letter proposes two methods to improve the iterative hard-reliability based majority-logic decoding algorithm for non-binary low-density parity-check (NB-LDPC) codes. The first method improves the error-correcting performance by modifying the initialization process, which is based on the fact that Gray coded modulation is used in general. In addition, a storage reduction method is proposed to make the proposed decoding hardware-friendly, which reduces the memory size considerably while sustaining the error-correcting performance achieved by the modified initialization. For an NB-LDPC code over Galois field of 32 elements, the memory size is reduced by about 75% compared with that of the conventional decoding algorithm.
The Low Density Parity Check (LDPC) are direct codes, which are true block and Shannon Limit codes.These codes are attained least error floors of data bits for data transfer applications used in communication systems.However, the proposed LDPC codes are more beneficial than Turbo codes because of reduction in the decoding complexity and detection of the errors in less cycle time.This results the reduction of decoding time, low decoding latency, complexity and as well as least error floorings in communication, when the transmitted data contains multiple error bits.This paper is proposed to represent the majority logic decoding/detecting of LDPC codes.This paper proposes the Generation of Originator and Parity estimated matrices for the Binary LDPC Codes.Here, the proposed techniques are hard decision decrypting and soft decision decrypting schemes.These schemes uses majority logic decoding based on the data transmission and reception in communication channel.This paper also elaborates the effective calculation of Euclidean distance and algorithm for constructing the LDPC codes.
Based on decoding performance,complexity and latency of finite-geometry low-density parity-check(FG-LDPC) codes,an efficient decoding algorithm is proposed.The new algorithm is a hybrid bit-flipping(BF)/majority-logic(MLG) decoding scheme.In BF decoding,an efficient method was explored to measure the reliability of the checks.At the completion of a small number of iterations,the output from BF decoding is decoded by MLG decoding.In the hybrid algorithm,there are no float operations.Simulation results show that the hybrid algorithm can provide 0.3?dB coding gain over weight bit-flipping(WBF) decoding.