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Conference proceedings - Canadian Conference on Electrical and Computer Engineering

Iterative decoding algorithm of lattices

Mohammad‐Reza Sadeghi, Amir H. Banihashemi, Daniel Panario

Published Nov 12, 2004• 5 citations
Publisher

Abstract

The so-called min-sum algorithm for iterative decoding of low-density parity-check (LDPC) codes is generalized to decode lattices. An upper bound on the decoding complexity per iteration is derived, and for LDPC lattices constructed by Construction D' and using a nested sequence of LDPC codes, exact values for computational complexity are also given. We show that iterative decoding of LDPC lattices has a reasonably low complexity such that lattices with dimensions of a few thousands can be easily decoded.

DOI
10.1109/ccece.2004.1349667

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The so-called min-sum algorithm for iterative decoding of low-density parity-check (LDPC) codes is generalized to decode lattices. An upper bound on the decoding complexity per iteration is derived, and for LDPC lattices constructed by Construction D' and using a nested sequence of LDPC codes, exact values for computational complexity are also given. We show that iterative decoding of LDPC lattices has a reasonably low complexity such that lattices with dimensions of a few thousands can be easily decoded.
The so-called min-sum algorithm has been applied for decoding lattices constructed by Construction D'. We generalize this iterative decoding algorithm to decode lattices constructed by Construction D. An upper bound on the decoding complexity per iteration, in terms of coding gain, label group sizes of the lattice and other factors is derived. We show that iterative decoding of LDGM lattices has a reasonably low complexity such that lattices with dimensions of a few thousands can be easily decoded.
Low-density parity-check codes (LDPC) can have an impressive performance under iterative decoding algorithms. In this paper we introduce a method to construct high coding gain lattices with low decoding complexity based on LDPC codes. To construct such lattices we apply Construction D', due to Bos, Conway, and Sloane, to a set of parity checks defining a family of nested LDPC codes. For the decoding algorithm, we generalize the application of max-sum algorithm to the Tanner graph of lattices. Bounds on the decoding complexity are derived and our analysis shows that using LDPC codes results in low decoding complexity for the proposed lattices. The progressive edge growth (PEG) algorithm is then extended to construct a class of nested regular LDPC codes which are in turn used to generate low density parity check lattices. Using this approach, a class of two-level lattices is constructed. The performance of this class improves when the dimension increases and is within 3 dB of the Shannon limit for error probabilities of about 10-6. This is while the decoding complexity is still quite manageable even for dimensions of a few thousands
Low-density parity-check (LDPC) codes can have a good performance under iterative decoding algorithms. This idea is used to construct a class of lattices with relatively high coding gain and low decoding complexity. To construct such lattices, Construction D' is applied to the set of parity check vectors of a class of nested LDPC codes. Bounds on the minimum distance and the coding gain of the corresponding lattice are provided. We also provide a practical way of finding the cross sections of the lattice given the parity check matrix of a lattice. The progressive edge growth algorithm is extended and is used to construct a class of nested binary codes to generate the corresponding lattice. Simulation results confirm the good performance of this class of lattice.
Abstract: In this paper, a fast-convergence algorithm is proposed for the decoding of low-density parity-check (LDPC) codes. By putting more weight on the message update from check node to variable node in current iteration, the proposed method speeds up the decoding significantly. Simulation results show that compared with the standard layered min-sum decoding algorithm, the proposed scheme may reduce about 1/6 iteration numbers for LDPC codes used in DVB-S2, with hardware complexity overhead less than 2%. Key–Words: LDPC code, fast convergence decoding algorithm, layered decoding, min-sum algorithm, hardware implementation 1
Among the decoding algorithms for low-density parity-check(LDPC) code,sum-product algorithm(SPA) has the optimal performance but high complexity,while min-sum algorithm has simple implementation complexity but worse performance.Considering this performance-complexity contradiction,some modified min-sum algorithms are proposed.In this paper,researches are done based on one of the modified min-sum algorithms that is close to SPA in performance but the way modifying fraction works is simplified.Simplified algorithm remains similar in performance to sum-product algorithm but has a remarkably reduced implementation complexity.