Abstract
A lattice in \(\mathbb {R}^{n}\) is a set of points (vectors) composed by all integer linear combinations of independent vectors.
Notes
- 1.
Some authors use the row convention of considering basis vectors as rows of a generator matrix; we follow here the column convention.
- 2.
In several textbooks and papers, the minimum norm is defined as the square of this number.
- 3.
Strictly speaking, there might be more than one closest vector to y, which might cause ambiguities. In order for Q Λ (y) to be well defined, one has to break the ties, i.e., to decide which “faces” of the Voronoi cell to use. In order to simplify notation, we will avoid such a technicality and consider that ties are broken according to some well-defined systematic rule. Considering this rule we will also, by abuse of notation, sometimes say “the” closest lattice point to y. Notice that the faces of the Voronoi cell (i.e., the ambiguous points) have measure zero in \(\mathbb {R}^n\).
- 4.
Or approximately 1.53, in decibels. This number is sometimes referred to as the ultimate shaping gain of a lattice.
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Costa, S.I.R., Oggier, F., Campello, A., Belfiore, JC., Viterbo, E. (2017). Lattices and Applications. In: Lattices Applied to Coding for Reliable and Secure Communications. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-319-67882-5_2
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