Solving Box-Constrained Integer Least Squares Problems

A box-constrained integer least squares problem (BILS) arises from several wireless communications applications. Solving a BILS problem usually has two stages: reduction (or preprocessing) and search. This paper presents a reduction algorithm and a search algorithm. Unlike the typical reduction algo...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2008-01, Vol.7 (1), p.277-287
Main Authors: Xiao-Wen Chang, Xiao-Wen Chang, Qing Han, Qing Han
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Channel coding
Coding, codes
Computer science
Cryptography
Decoding
Exact sciences and technology
Information, signal and communications theory
Integers
Lattices
Least squares method
Least squares methods
MIMO
Monte Carlo methods
Preprocessing
Radar imaging
Reduction
Search algorithms
Searching
Signal and communications theory
Telecommunications and information theory
Wireless communication
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Summary:A box-constrained integer least squares problem (BILS) arises from several wireless communications applications. Solving a BILS problem usually has two stages: reduction (or preprocessing) and search. This paper presents a reduction algorithm and a search algorithm. Unlike the typical reduction algorithms, which use only the information of the lattice generator matrix, the new reduction algorithm also uses the information of the given input vector and the box constraint and is very effective for search. The new search algorithm overcomes some shortcomings of the existing search algorithms and gives some other improvement. Simulation results indicate the combination of the new reduction algorithm and the new search algorithm can be much more efficient than the existing algorithms, in particular when the least squares residual is large.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2008.060497