English

Lattice (List) Decoding Near Minkowski's Inequality

Information Theory 2021-09-13 v2 Data Structures and Algorithms math.IT

Abstract

Minkowski proved that any nn-dimensional lattice of unit determinant has a nonzero vector of Euclidean norm at most n\sqrt{n}; in fact, there are 2Ω(n)2^{\Omega(n)} such lattice vectors. Lattices whose minimum distances come close to Minkowski's bound provide excellent sphere packings and error-correcting codes in Rn\mathbb{R}^{n}. The focus of this work is a certain family of efficiently constructible nn-dimensional lattices due to Barnes and Sloane, whose minimum distances are within an O(logn)O(\sqrt{\log n}) factor of Minkowski's bound. Our primary contribution is a polynomial-time algorithm that list decodes this family to distances approaching 1/21/\sqrt{2} of the minimum distance. The main technique is to decode Reed-Solomon codes under error measured in the Euclidean norm, using the Koetter-Vardy "soft decision" variant of the Guruswami-Sudan list-decoding algorithm.

Keywords

Cite

@article{arxiv.2010.04809,
  title  = {Lattice (List) Decoding Near Minkowski's Inequality},
  author = {Ethan Mook and Chris Peikert},
  journal= {arXiv preprint arXiv:2010.04809},
  year   = {2021}
}

Comments

14 pages, 2 figures

R2 v1 2026-06-23T19:13:25.357Z