Low-density parity-check lattices: Construction and decoding analysis

被引:65
|
作者
Sadeghi, Mohammad-Reza [1 ]
Banihashemi, Amir H.
Panario, Daniel
机构
[1] Amirkabir Univ Technol, Fac Math & Comp Sci, Tehran, Iran
[2] Carleton Univ, Dept Syst & Comp Engn, BCWS Ctr, Ottawa, ON K1S 5B6, Canada
[3] Carleton Univ, Sch Math & Stat, Ottawa, ON K1S 5B6, Canada
关键词
additive white Gaussian noise (AWGN) channel; iterative decoding; lattice codes; lattices; low-density parity-check (LDPC) codes; low-density parity-check (LDPC) lattices; min-sum algorithm; progressive-edge growth (PEG) construction; Tanner graphs;
D O I
10.1109/TIT.2006.881720
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:4481 / 4495
页数:15
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