Boosted KZ and LLL Algorithms

There exist two issues among popular lattice reduction algorithms that should cause our concern. The first one is Korkine-Zolotarev (KZ) and Lenstra-Lenstra-Lovász (LLL) algorithms may increase the lengths of basis vectors. The other is KZ reduction suffers worse performance than Minkowski reductio...

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Veröffentlicht in:IEEE transactions on signal processing 2017-09, Vol.65 (18), p.4784-4796
Hauptverfasser: Lyu, Shanxiang, Ling, Cong
Format: Artikel
Sprache:eng
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Zusammenfassung:There exist two issues among popular lattice reduction algorithms that should cause our concern. The first one is Korkine-Zolotarev (KZ) and Lenstra-Lenstra-Lovász (LLL) algorithms may increase the lengths of basis vectors. The other is KZ reduction suffers worse performance than Minkowski reduction in terms of providing short basis vectors, despite its superior theoretical upper bounds. To address these limitations, we improve the size reduction steps in KZ and LLL to set up two new efficient algorithms, referred to as boosted KZ and LLL, for solving the shortest basis problem with exponential and polynomial complexity, respectively. Both of them offer better actual performance than their classic counterparts, and the performance bounds for KZ are also improved. We apply them to designing integer-forcing (IF) linear receivers for multi-input multioutput communications. Our simulations confirm their rate and complexity advantages.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2017.2708020