89,534 research outputs found
PotLLL: A Polynomial Time Version of LLL With Deep Insertions
Lattice reduction algorithms have numerous applications in number theory,
algebra, as well as in cryptanalysis. The most famous algorithm for lattice
reduction is the LLL algorithm. In polynomial time it computes a reduced basis
with provable output quality. One early improvement of the LLL algorithm was
LLL with deep insertions (DeepLLL). The output of this version of LLL has
higher quality in practice but the running time seems to explode. Weaker
variants of DeepLLL, where the insertions are restricted to blocks, behave
nicely in practice concerning the running time. However no proof of polynomial
running time is known. In this paper PotLLL, a new variant of DeepLLL with
provably polynomial running time, is presented. We compare the practical
behavior of the new algorithm to classical LLL, BKZ as well as blockwise
variants of DeepLLL regarding both the output quality and running time.Comment: 17 pages, 8 figures; extended version of arXiv:1212.5100 [cs.CR
Certified lattice reduction
Quadratic form reduction and lattice reduction are fundamental tools in
computational number theory and in computer science, especially in
cryptography. The celebrated Lenstra-Lenstra-Lov\'asz reduction algorithm
(so-called LLL) has been improved in many ways through the past decades and
remains one of the central methods used for reducing integral lattice basis. In
particular, its floating-point variants-where the rational arithmetic required
by Gram-Schmidt orthogonalization is replaced by floating-point arithmetic-are
now the fastest known. However, the systematic study of the reduction theory of
real quadratic forms or, more generally, of real lattices is not widely
represented in the literature. When the problem arises, the lattice is usually
replaced by an integral approximation of (a multiple of) the original lattice,
which is then reduced. While practically useful and proven in some special
cases, this method doesn't offer any guarantee of success in general. In this
work, we present an adaptive-precision version of a generalized LLL algorithm
that covers this case in all generality. In particular, we replace
floating-point arithmetic by Interval Arithmetic to certify the behavior of the
algorithm. We conclude by giving a typical application of the result in
algebraic number theory for the reduction of ideal lattices in number fields.Comment: 23 page
Dual-lattice ordering and partial lattice reduction for SIC-based MIMO detection
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we propose low-complexity lattice detection algorithms for successive interference cancelation (SIC) in multi-input multi-output (MIMO) communications. First, we present a dual-lattice view of the vertical Bell Labs Layered Space-Time (V-BLAST) detection. We show that V-BLAST ordering is equivalent to applying sorted QR decomposition to the dual basis, or equivalently, applying sorted Cholesky decomposition to the associated Gram matrix. This new view results in lower detection complexity and allows simultaneous ordering and detection. Second, we propose a partial reduction algorithm that only performs lattice reduction for the last several, weak substreams, whose implementation is also facilitated by the dual-lattice view. By tuning the block size of the partial reduction (hence the complexity), it can achieve a variable diversity order, hence offering a graceful tradeoff between performance and complexity for SIC-based MIMO detection. Numerical results are presented to compare the computational costs and to verify the achieved diversity order
Geodesic continued fractions and LLL
We discuss a proposal for a continued fraction-like algorithm to determine
simultaneous rational approximations to real numbers
. It combines an algorithm of Hermite and Lagarias
with ideas from LLL-reduction. We dynamically LLL-reduce a quadratic form with
parameter as . The new idea in this paper is that checking
the LLL-conditions consists of solving linear equations in
- âŠ