## Abstract

Most of the existing methods that are used to solve the closest lattice point problem are based on an efficient search of the lattice points. In this paper a novel alternative approach is suggested where the closest point to a given vector is found by calculating which Voronoi cell contains this vector in an iterative manner. Each iteration is made of simple "slicing" operations, using a list of the Voronoi relevant vectors that define the basic Voronoi cell of the lattice. The algorithm is guaranteed to converge to the closest lattice point in a finite number of steps. The method is suitable, for example, for decoding of multi-input multi-output (MIMO) communication problems. The average computational complexity of the proposed method is comparable to that of the efficient variants of the sphere decoder, but its computational variability is smaller.

Original language | English |
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Pages (from-to) | 715-731 |

Number of pages | 17 |

Journal | SIAM Journal on Discrete Mathematics |

Volume | 23 |

Issue number | 2 |

DOIs | |

State | Published - 2009 |

## Keywords

- Closest neighbor
- Closest point search
- Lattice
- Lattice codes
- Lattice decoding
- Lattice quantization
- Voronoi relevant vectors