Improvements in closest point search based on dual HKZ-bases ?
In this paper we review the technique to solve the CVP based on dual HKZ-bases by J. Blmer [4]. The technique is based on the transference theorems given by Banaszczyk [3] which imply some necessary conditions on the coefficients of the closest vectors with respect to a basis whose dual is HKZ-reduced. Recursively, starting with the last coefficient, intervals of length i can be derived for the i-th coefficient of any closest vector. This leads to n ! candidates for closest vectors. In this paper we refine the necessary conditions derived from the transference theorems, giving an exponential reduction of the number of candidates. The improvement is due to the fact that the lengths of the intervals are not independent. In the original algorithm the candidates for a coefficient pair (vi,vi+1) ( v i , v i + 1 ) correspond to the integer points in a rectangle of volume i?(i+1) i ? ( i + 1 ) . In our analysis we show that the candidates for (vi,vi+1) ( v i , v i + 1 ) in fact lie in an ellipse with transverse and conjugate diameter i+1 i + 1 , respectively i . This reduces the expected number of points to be enumerated by an exponential factor of about 0.886n 0.886 n . We further show how a choice of the coefficients (vn,,vi+1) ( v n ,  , v i + 1 ) influences the interval from which vi v i can be chosen. Numerical computations show that these considerations allow to bound the expected number of points to be enumerated by n0.75n n 0.75 n for 10?n?2000 10 ? n ? 2000 . Under the assumption that the Gaussian heuristic for the length of the shortest nonzero vector in a lattice is tight, this number can even be bounded by 1 2 2 n n n / 2 .
cvp dual lattice lattice problems nearest point search