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IEEE International Black Sea Conference on Communications and Networking

Asymptotic and finite-length performance of irregular spatially-coupled codes

Reza A. Ashrafi, Abdullah Sarıduman, Alí Emre Pusane

Published May 1, 2014• 1 citation

Abstract

The newest family of low-density parity-check (LDPC) codes, spatially-coupled (SC) codes, is shown to have several desirable characteristics including low implementation complexity and close-to-optimal performance over a range of channels. Furthermore, because of their ribbon-shaped parity-check matrices, window decoding can be used to decode these codes, which leads to low-delay implementations. Researchers have focused on asymptotically regular SC code ensembles and have examined several aspects of the code construction processes. In this paper, we concentrate on irregular SC code ensembles. We evaluate their decoding thresholds over the binary erasure channel and show that their performance is better than their regular SC counterparts. It is also shown that the gap between asymptotic coding thresholds of irregular SC ensembles and the fundamental Shannon limit gets negligibly small. For the sake of a better comparison, we have also evaluated the finite-length error performance of selected regular and irregular SC codes over the additive white Gaussian channel and it is also observed that finite-length error performance of these irregular SC codes outperforms regular SC codes. To further improve the error performance of these codes and to lower the possible error floors, progressive edge growth algorithm has also been considered in the finite-length performance analysis.

DOI: 10.1109/blackseacom.2014.6849017

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The finite-length performance of multi-edge spatially coupled low-density parity-check (SC-LDPC) codes over the binary erasure channel (BEC) is analyzed. Existing scaling laws are extended to arbitrary protograph base matrices that include puncturing patterns and multiple edges between nodes. A regular protograph-based SC-LDPC construction based on the (4; 8)-regular LDPC block code works well in the waterfall region compared to more involved rate-1/2 structures proposed to improve the threshold to minimum distance trade-off. Scaling laws are also used for code design and to estimate the block length of a given SC-LDPC code ensemble to match the performance of some other code. Estimates on the performance degradation are developed if the chain length varies.

Spatially-coupled (SC) LDPC codes are constructed from a set of L regular sparse codes of length M. In the asymptotic limit of these parameters, SC codes present an excellent decoding threshold under belief propagation (BP) decoding, close to the maximum a posteriori (MAP) threshold of the underlying regular code. In the finite-length regime, we need both dimensions, L and M, to be sufficiently large, yielding a very large code length and decoding latency. In this paper, and for the erasure channel, we show that the finite-length performance of SC codes is improved if we consider the tree-structured expectation propagation (TEP) algorithm in the decoding stage. When applied to the decoding of SC LDPC codes, it allows using shorter codes to achieve similar error rates. We also propose a window-sliding scheme for the TEP decoder to reduce the decoding latency.

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Spatially-coupled low-density parity-check (SC-LDPC) codes are known to have excellent asymptotic properties. Much less is known regarding their finite-length performance. We propose a scaling law to predict the error probability of finite-length spatially coupled code ensembles when transmission takes place over the binary erasure channel. We discuss how the parameters of the scaling law are connected to fundamental quantities appearing in the asymptotic analysis of these ensembles and we verify that the predictions of the scaling law fit well to the data derived from simulations over a wide range of parameters. The ultimate goal of this line of research is to develop analytic tools for the design of SC-LDPC codes under practical constraints.