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International Conference on Communications

Analysis of Absorbing Sets for Array-Based LDPC Codes

Lara Dolecek, Zhengya Zhang, Venkat Anantharam, Martin J. Wainwright, Borivoje Nikolić

Published Jun 1, 2007• 96 citations
Publisher

Abstract

Low density parity check codes (LDPC) are known to perform very well under iterative decoding. However, these codes also exhibit a change in the slope of the bit error rate (BER) vs. signal to noise ratio (SNR) curve in the very low BER region. In our earlier work using hardware emulation in this deep BER regime we argue that this behavior can be attributed to specific structures within the Tanner graph associated with an LDPC code, called absorbing sets. In this paper we provide a detailed theoretical analysis of absorbing sets for array-based LDPC codes Cp.gamma. Specifically, we identify and enumerate all the smallest absorbing sets for these array-based LDPC codes with gamma = 2,3,4 with standard parity check matrix. Experiments carried out on the emulation platform show excellent agreement with our theoretical results.

DOI
10.1109/icc.2007.1037

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Low density parity check codes (LDPC) are known to perform very well under iterative decoding. However, these codes also exhibit a change in the slope of the bit error rate (BER) vs. signal to noise ratio (SNR) curve in the very low BER region. In our earlier work using hardware emulation in this deep BER regime we argue that this behavior can be attributed to specific structures within the Tanner graph associated with an LDPC code, called absorbing sets. In this paper we provide a detailed theoretical analysis of absorbing sets for array-based LDPC codes Cp.gamma. Specifically, we identify and enumerate all the smallest absorbing sets for these array-based LDPC codes with gamma = 2,3,4 with standard parity check matrix. Experiments carried out on the emulation platform show excellent agreement with our theoretical results.
The class of low-density parity-check (LDPC) codes is attractive, since such codes can be decoded using practical message-passing algorithms, and their performance is known to approach the Shannon limits for suitably large block lengths. For the intermediate block lengths relevant in applications, however, many LDPC codes exhibit a so-called “error floor,” corresponding to a significant flattening in the curve that relates signal-to-noise ratio (SNR) to the bit-error rate (BER) level. Previous work has linked this behavior to combinatorial substructures within the Tanner graph associated with an LDPC code, known as (fully) absorbing sets. These fully absorbing sets correspond to a particular type of near-codewords or trapping sets that are stable under bit-flipping operations, and exert the dominant effect on the low BER behavior of structured LDPC codes. This paper provides a detailed theoretical analysis of these (fully) absorbing sets for the class ofCp,γC_{p, \gamma}Cp,γ​array-based LDPC codes, including the characterization of all minimal (fully) absorbing sets for the array-based LDPC codes forγ=2,3,4\gamma = 2,3,4γ=2,3,4, and moreover, it provides the development of techniques to enumerate them exactly. Theoretical results of this type provide a foundation for predicting and extrapolating the error floor behavior of LDPC codes.
Many classes of high-performance low-density parity-check (LDPC) codes are based on parity check matrices composed of permutation submatrices. We describe the design of a parallel-serial decoder architecture that can be used to map any LDPC code with such a structure to a hardware emulation platform. High-throughput emulation allows for the exploration of the low bit-error rate (BER) region and provides statistics of the error traces, which illuminate the causes of the error floors of the (2048, 1723) Reed-Solomon based LDPC (RS-LDPC) code and the (2209, 1978) array-based LDPC code. Two classes of error events are observed: oscillatory behavior and convergence to a class of non-codewords, termed absorbing sets. The influence of absorbing sets can be exacerbated by message quantization and decoder implementation. In particular, quantization and the log-tanh function approximation in sum-product decoders
Absorbing sets are combinatorially defined objects existing in the Tanner graph of a low-density parity-check (LDPC) code that have been shown to cause failures in the iterative message-passing decoder when transmission occurs over the additive white Gaussian noise channel. In this paper, we study the absorbing set properties of a class of high-rate array-based spatially coupled LDPC (SC-LDPC) codes that are constructed by coupling together L array-based LDPC block codes. We prove that the smallest absorbing sets existing in the Tanner graph of the SC-LDPC code have the same size as those in the corresponding uncoupled LDPC codes, and the number of such sets grow linearly with L. We show that spatial coupling greatly reduces the average number (per symbol) of minimal sets compared to the uncoupled codes, and we explain that this reduction is due to many absorbing sets and small cycles being `broken' by the coupling process. The large reduction in the number of minimal absorbing sets suggests that array-based SC-LDPC codes will have significantly improved decoding performance in the high signal-to-noise ratio regime compared to the corresponding uncoupled LDPC codes.
Abstract—Many classes of high-performance low-density parity-check (LDPC) codes are based on parity check matrices composed of permutation submatrices. We describe the design of a parallel-serial decoder architecture that can be used to map any LDPC code with such a structure to a hardware emulation platform. High-throughput emulation allows for the exploration of the low bit-error rate (BER) region and provides statistics of the error traces, which illuminate the causes of the error floors of the (2048, 1723) Reed-Solomon based LDPC (RS-LDPC) code and the (2209, 1978) array-based LDPC code. Two classes of error events are observed: oscillatory behavior and convergence to a class of non-codewords, termed absorbing sets. The influence of absorbing sets can be exacerbated by message quantization and decoder implementation. In particular, quantization and the log-tanh function approximation in sum-product decoders
Absorbing sets are combinatorial structures in the Tanner graphs of low-density parity-check (LDPC) codes that have been shown to inhibit the high signal-to-noise ratio performance of iterative decoders over many communication channels. Absorbing sets of minimum size are the most likely to cause errors, and thus have been the focus of much research. In this paper, we determine the sizes of absorbing sets that can occur in general and left-regular LDPC code graphs, with emphasis on the range of $ b $ for a given $ a $ for which an $ (a,b) $-absorbing set may exist. We identify certain cases of extremal absorbing sets that are elementary, a particularly harmful class of absorbing sets, and also introduce the notion of minimal absorbing sets which will help in designing absorbing set removal algorithms.
Absorbing sets, a class of combinatorial structures of the Tanner graph representation of a low-density parity-check (LDPC) code, are known to influence the performance of the code under message passing iterative decoding. In this paper, we study the smallest absorbing sets of LDPC codes constructed from projective planes and Euclidean planes. The lower bounds on the parameters of smallest absorbing sets given by Dolecek are proven to be tight for these two families of LDPC codes. We also analyze the combinatorial properties of the smallest absorbing sets and give conditions necessary and sufficient for a set of bit nodes in the Tanner graph to be a smallest absorbing set. For LDPC codes from projective planes, we further give a condition necessary and sufficient for a smallest absorbing set to be a fully absorbing set. In addition, we show that these smallest absorbing sets are asymptotically not stable, which may explain to some extent the good performance as well as the low error floor expectation of these two families of LDPC codes.