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Communications technology

Study on Decoding Algorithm for Non-Binary LDPC Codes

Lei Wen

Published Jan 1, 2011• 0 citations
OpenAlex

Abstract

Non-binary LDPC codes are obtained by generalizing binary LDPC coeds from finite field GF(2) to finite field GF(q).Its elements of parity check matrix are not(0,1),but ensemble(0,1,…,q-1),and its decoding method still employs belief propagation and iterative algorithm.This paper mainly derives the iterative formulas of decoding algorithm for Non-Binary LDPC codes and analyzes an improved algorithm based on FFT.Finally,the predominant performance of FFT decoding algorithm is verified by simulation.

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Non-binary LDPC codes are obtained by generalizing binary LDPC coeds from finite field GF(2) to finite field GF(q).Its elements of parity check matrix are not(0,1),but ensemble(0,1,…,q-1),and its decoding method still employs belief propagation and iterative algorithm.This paper mainly derives the iterative formulas of decoding algorithm for Non-Binary LDPC codes and analyzes an improved algorithm based on FFT.Finally,the predominant performance of FFT decoding algorithm is verified by simulation.
The non-binary LDPC is the promotion to the finite GF(q) of binary LDPC codes.The parity check matrix elements is no longer 0 and 1,but collections(0,1,2,…,q-1),while the decoding still uses the efficient iterative decoding based on belief propagation algorithm.This paper focuses on the check matrix of structure of the quasi-cyclic LDPC codes(QC-LDPC) as well as the min-sum decoding algorithm.Then the LDPC codes decoding performance is simulated under different conditions in white Gaussian noise channel(AWGN) with Matlab.Finally,the impact of non-binary LDPC Decoding performance factors is analyzed.
Low density parity check (LDPC) code is a kind of linear block code with excellent performance which is proposed by Dr. Gallager. It overcomes the shortcomings of other error correcting codes and it is the nearest channel code from Shannon limit at the present discover. The decoding algorithms of L DPC code can reduce the decoding delay by the parallel decoding structure, so this has caused great concern in many fields. In recent years more and more scholars begin to study LDPC code, this makes the coding and decoding algorithms of LDPC code improved continuously. LDPC code has been widely used in many fields such as optical fiber communication, digital watermarking, underwater communication and deep space communication because of its excellent performance. Non-binary LDPC code has better performance compared with binary LDPC code. In this paper, FFT-BP decoding algorithm of non-binary LDPC code is studied, and on this basis, we proposed an improved FFT-BP algorithm. The improved decoding algorithm can effectively reduce the average iteration number. Finally, we achieved encode and decode algorithm of non-binary LDPC code with FPGA.
Low Density Parity Check (LDPC) codes have excellent error correcting performance. LDPC codes are one of the block coding techniques and it performs near Shannon limit and recommended for many practical applications. Non-binary LDPC codes extension of binary LDPC in error correcting property especially for short and moderate block length. In many digital communication systems these codes have strong competitors of turbo codes for error control. Low Density Parity Check as it name is suggests that in a parity check matrix (H) consists of very small number of non-zero elements comparing with zero elements. The strength of the LDPC code defines Parity Check Matrix (PCM). LDPC code contains two types of decoding algorithms hard and soft decision algorithm. By comparing with other traditional decoding algorithm FFT based sum product algorithm reduced computation complexity with better decoding performance. In this paper, LDPC codes for FFT based sum product decoding algorithm performances are analysed for various order of Galois Field GF(q) using AWGN channel. Decoding performance measured in terms of symbol error rate which improve with increasing order of Galois field.
Low-density parity-check (LDPC) codes over finite fields GF(q) have a better performance than those of the binary low-density parity-check codes, at short and medium block lengths, but the decoder of GF(q)-LDPC has more complexity. In this paper, we present a new reduced-complexity belief propagation (BP) decoding algorithm for GF(q)-LDPC codes by analyzing the reliability of code symbols. Instead of update all the variable nodes during iteration, we just update variable nodes which are mostly to be in an error. The algorithm also shows a property to reduce the effects of oscillating on decoding. The simulations prove that we could improve performance and reduce complexity at the same time for short and medium GF(q)-LDPC codes.
Non-binary LDPC (NB-LDPC) codes has inherent parallelism and excellent error correcting performance. By comparing with other traditional algorithm, FFT-SPA based non-binary LDPC code gives reduced computation complexity with better decoding performance. In this paper, FFT-SPA based NB-LDPC decoding performance is analyzed for the specification of IEEE 802.11n standard. Parity check matrix (PCM) defines the strength of the LDPC codes. By retaining the properties of the PCM structures, in this paper we propose two modified parity check matrices to reduce the computation strength. For various order of Galois Field with different PCM structures, non-binary LDPC codes performances are analyzed.
The problem of low-complexity linear programming (LP) decoding of nonbinary low-density parity-check (LDPC) codes is considered, and an iterative LP decoding algorithm is presented. Results that were previously derived for binary LDPC codes are extended to the nonbinary case. Both simple and generalized nonbinary LDPC codes are considered. It is shown how the algorithm can be implemented efficiently using a finite-field fast Fourier transform. Then, the convergence rate of the algorithm is analyzed. The complexity of the algorithm scales linearly in the block length, and it can approximate, up to an arbitrarily small relative error, the objective function of the exact LP solution. When applied to a typical code from an appropriate nonbinary LDPC code ensemble, the algorithm can correct a constant fraction of errors in linear (in the block length) computational complexity. Computer experiments with the new iterative LP decoding algorithm show that, in the error floor region, it can have better performance compared to belief propagation decoding, with similar computational requirements.