A set of formulas were developed describe the probability of the minimum Hamming distance and the relationship between the bit error ratio and the minimum Hamming distance for low-density parity-check(LDPC) codes constructed with basic matrix expansion algorithm to analyze the error-floor problem.A block interleaving algorithm was given that permits sub-matrices to be superposed in the same location to construct low-error-floor LDPC codes.Simulation results demonstrate that compared with the basic matrix expansion algorithm,the proposed code construction algorithm alleviates the error-floor of an LDPC code from 10-7 to 10-9.
A set of formulas were developed describe the probability of the minimum Hamming distance and the relationship between the bit error ratio and the minimum Hamming distance for low-density parity-check(LDPC) codes constructed with basic matrix expansion algorithm to analyze the error-floor problem.A block interleaving algorithm was given that permits sub-matrices to be superposed in the same location to construct low-error-floor LDPC codes.Simulation results demonstrate that compared with the basic matrix expansion algorithm,the proposed code construction algorithm alleviates the error-floor of an LDPC code from 10-7 to 10-9.
There are many algorithms to construct good low-density parity-check (LDPC) code, the most typical algorithms are bit-filling algorithm, randomly construction algorithm, and PEG (progressive edge growth) algorithm. As shown in [1], the error floor of LDPC Code is decreased by using PEG algorithm, but the error correction performance in waterfall region is compromised since a stopping set with small size will form the codeword with small Hamming weight over AWGN [2]. In this paper, we propose a novel algorithm to construct LDPC Codes. In our algorithm, we construct LDPC Code to avoid small girth and small stopping set by detecting the complete associated matrix of check node (defined in this paper) that converted from bipartite graph of LDPC Code based on the graph theory. Simulation shows that the LDPC code constructed by our algorithm has lower error floor than randomly constructed LDPC Code. The performance improvement of our algorithm is 0.1dB at BER of 10-3compared with PEG algorithm.
Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.
Introduction In this chapter we introduce low-density parity-check (LDPC) codes, a class of error correction codes proposed by Gallager in his 1962 PhD thesis 12 years after error correction codes were first introduced by Hamming (published in 1950). Both Hamming codes and LDPC codes are block codes: the messages are broken up into blocks to be encoded at the transmitter and similarly decoded as separate blocks at the receiver. While Hamming codes are short and very structured with a known, fixed, error correction ability, LDPC codes are the opposite, usually long and often constructed pseudo-randomly with only a probabilistic notion of their expected error correction performance. The chapter begins by presenting parity bits as a means to detect and, when more than one is employed, to correct errors in digital data. Block error correction codes are described as a linear combination of parity-check equations and thus defined by their parity-check matrix representation. The graphical representation of codes by Tanner graphs is presented and the necessary graph theoretic concepts introduced. In Section 2.4 iterative decoding algorithms are introduced using a hard decision algorithm (bit flipping), so that the topic is developed first without reference to probability theory. Subsequently the sum–product decoding algorithm is presented. This chapter serves as a self-contained introduction to LDPC codes and their decoding. It is intended that the material presented here will enable the reader to implement LDPC encoders and iterative decoders.
Only since the mid-1990s, with the increase in computational power, has the\nimportance been realized regarding low-density parity-check (LDPC) codes as leading error\ncorrecting codes. The work in this thesis primarily studies LDPC codes that are de???ned by a\nparity-check matrix comprised of r _ r permutation matrix blocks, that is, permutation-block\nLDPC codes. More specifically, we study their minimum Hamming distance, as this is a\nparameter that affects the performance of linear codes, and thus LDPC codes.\nIt has been proven that there are upper bounds on the minimum Hamming distance of\nquasi-cyclic codes, de???ned by a parity-check matrix comprised of r _ r circulant matrix\nblocks, regardless of how large we allow r. However, we show that if general permutation\nmatrices are used instead of circulant matrices, we are able to exceed the bounds allowed by\nquasi-cyclic codes. Graphical representations of the codes, called Tanner-graphs, are used in\nproving many useful results regarding permutation-block LDPC codes and their minimum\nHamming distance. We show a characterization of the minimum Hamming distance of these\ncodes and we produce an algorithm for constructing permutation-block LDPC codes with\nlarge minimum Hamming distance.
To reduce the cycles in the Tanner graph which may affect the code performance,a recursive method to construct low-density parity-check(LDPC) codes was proposed.The method used a parity-check matrix of a short LDPC code as its mother matrix upon which a long code was constructed with circulant permutation matrices.By choosing the circulant permutation matrix parameters properly,the number of cycles having a given length in the Tanner graph of the constructed long codes were equal to or less than that of the short code.Either regular or irregular LDPC codes were constructed.Simulation results show that the LDPC codes constructed by this method have very low error-floor and almost no performance degradation due to their special structure as compared with random LDPC codes.
In order to construct nonbinary low-density parity-check(LDPC) codes with good waterfall and error floor properties,a method to improve the minimum Hamming distance of a class of nonbinary quasi-cyclic(QC) LDPC codes is presented.Two upper bounds on the minimum Hamming distance are derived for the nonbinary QC LDPC codes whose parity-check matrices consist of weight-2 columns.A special base matrix design allowing linear encoding in a parallel manner is also proposed.In addition,the design principals are given,according to which,the parallel and efficiently encodable codes reaching the upper bound on the minimum Hamming distance can be developed.Simulation shows that the proposed codes have both good waterfall and error floor properties.