In this paper, we analyze the size of the smallest stopping set (called the stopping distance) for the parity-check matrix of a superposed array low-density parity-check (SA-LDPC) code for column weights 3 and 4 by using the transversal design (TD) concept. An SA-LDPC code is obtained as the result of an n-fold recursive product operation (a superposition method) on the parity-check matrix of an array low-density parity-check (array LDPC) code, Hn(m, q), where n ≥ 2 and m and q are column and row weights, respectively. We provide the lower and upper bounds for the stopping distance of these codes. Our simulation result shows that the SA-LDPC codes can compete with the TD-LDPC codes, random LDPC codes, and lattice LDPC codes of comparable rates and lengths and can improve the error floor region of the bit error rate curve.
In this paper, we analyze the size of the smallest stopping set (called the stopping distance) for the parity-check matrix of a superposed array low-density parity-check (SA-LDPC) code for column weights 3 and 4 by using the transversal design (TD) concept. An SA-LDPC code is obtained as the result of an n-fold recursive product operation (a superposition method) on the parity-check matrix of an array low-density parity-check (array LDPC) code, Hn(m, q), where n ≥ 2 and m and q are column and row weights, respectively. We provide the lower and upper bounds for the stopping distance of these codes. Our simulation result shows that the SA-LDPC codes can compete with the TD-LDPC codes, random LDPC codes, and lattice LDPC codes of comparable rates and lengths and can improve the error floor region of the bit error rate curve.
In this paper, we study the minimum/stopping distance of array low-density parity-check (LDPC) codes. An array LDPC code is a quasi-cyclic LDPC code specified by two integers q and m, where q is an odd prime and m q. In the literature, the minimum/stopping distance of these codes (denoted by d(q, m) and h(q, m), respectively) has been thoroughly studied for m 5. Both exact results, for small values of q and m, and general (i.e., independent of q) bounds have been established. For m = 6, the best known minimum distance upper bound, derived by Mittelholzer, is d(q, 6) 32. In this paper, we derive an improved upper bound of d(q, 6) 20 and a new upper bound d(q, 7) 24 by using the concept of a template support matrix of a codeword/stopping set. The bounds are tight with high probability in the sense that we have not been able to find codewords of strictly lower weight for several values of q using a minimum distance probabilistic algorithm. Finally, we provide new specific minimum/stopping distance results for m 7 and low-to-moderate values of q ≤79.
In this work, we study the minimum/stopping distance of array low-density parity-check (LDPC) codes. An array LDPC code is a quasi-cyclic LDPC code specified by two integers q and m, where q is an odd prime and m <= q. In the literature, the minimum/stopping distance of these codes (denoted by d(q,m) and h(q,m), respectively) has been thoroughly studied for m <= 5. Both exact results, for small values of q and m, and general (i.e., independent of q) bounds have been established. For m=6, the best known minimum distance upper bound, derived by Mittelholzer (IEEE Int. Symp. Inf. Theory, Jun./Jul. 2002), is d(q,6) <= 32. In this work, we derive an improved upper bound of d(q,6) <= 20 and a new upper bound d(q,7) <= 24 by using the concept of a template support matrix of a codeword/stopping set. The bounds are tight with high probability in the sense that we have not been able to find codewords of strictly lower weight for several values of q using a minimum distance probabilistic algorithm. Finally, we provide new specific minimum/stopping distance results for m <= 7 and low-to-moderate values of q <= 79.
On the binary erasure channel (BEC), the performance of low-density parity-check (LDPC) codes decoded by iterative algorithms is estimated by the small stopping sets in the codes. The size of smallest stopping set is called the stopping distance. Since it depends on the structure of parity-check matrix for the code, we can construct the parity-check matrix by adding dependent rows so that the stopping distance is equal to the minimum distance. The stopping redundancy is defined as the smallest number of rows in such a parity-check matrix. In this paper, we propose a probabilistic algorithm for computing the stopping redundancy of LDPC codes. Additionally, we show numerical results of computing the stopping redundancy of (155,64), (504,252) and (1008,504) LDPC codes.
This paper examines the construction of low-density parity-check (LDPC) codes from transversal designs based on sets of mutually orthogonal Latin squares (MOLS). By transferring the concept of configurations in combinatorial designs to the level of Latin squares, we thoroughly investigate the occurrence and avoidance of stopping sets for the arising codes. Stopping sets are known to determine the decoding performance over the binary erasure channel and should be avoided for small sizes. Based on large sets of simple-structured MOLS, we derive powerful constraints for the choice of suitable subsets, leading to improved stopping set distributions for the corresponding codes. We focus on LDPC codes with column weight 4, but the results are also applicable for the construction of codes with higher column weights. Finally, we show that a subclass of the presented codes has quasi-cyclic structure which allows low-complexity encoding.
It is known that redundant parity-check equations can improve the performance of an LDPC code by reducing the number of harmful substructures in the parity-check matrix. However, it is a difficult problem to design a parity-check matrix in such a way that it avoids substructures that are known to be harmful to iterative decoding while keeping the number of redundant parity-check equations moderate and ensuring other desirable properties. We explicitly give redundant parity-check matrices for cyclic regular LDPC codes of length n and minimum distance d ~ √n in which there are only n parity-check equations but no stopping sets of size d+1 or smaller except for those that correspond to the nonzero codewords of the smallest weight. We do this by showing that the well-known projective LDPC codes from the incidence matrices of projective planes PG(2, q) with q even have this property. This result may give insight into how the small number of redundant parity-check equations in the geometric LDPC codes may be contributing to the good performance reported in the literature. We also give a slightly improved upper bound on the size of a smallest generic erasure correcting set.
Traditionally, low-density parity-check (LDPC) codes are constructed randomly and it is not clear whether algebraically constructed codes, such as cyclic codes, can compete with the error correction performances of the random codes. We consider in this paper new cyclic low-density parity-check codes decoded with the sum-product algorithm. The cyclic codes we present have sparse parity-check matrices, good minimum distance and girth 6. Using frnite-length analysis and simulation results we show that the most significant benefit of the new codes, in terms of error correction performance, is the linearly dependent rows in their parity-check matrices. Our results suggest that increasing column weight to improve the minimum distance and the minimum stopping set size of the code proves beneficial at low erasure probabilities but adversely affects performance in channels with high erasure probabilities.