DocumentCode
1062487
Title
Partial regularisation approach for detection problems in underdetermined linear systems
Author
Chang, X.-W. ; Yang, Xu ; Le-Ngoc, Tho ; Wang, Peng
Author_Institution
Sch. of Comput. Sci., McGill Univ., Montreal, QC
Volume
3
Issue
1
fYear
2009
fDate
1/1/2009 12:00:00 AM
Firstpage
17
Lastpage
24
Abstract
The maximum likelihood detection problem in many underdetermined linear communications systems can be described as an underdetermined integer least squares (ILS) problem. To solve it efficiently, a partial regularisation approach is proposed. The original underdetermined ILS problem is first transformed to an equivalent overdetermined ILS problem by using part of the transmit vector to do the regularisation. Then the overdetermined ILS problem is solved by conventional sphere decoding algorithms. Simulation results indicate that this approach can be much more efficient than other approaches for any square constellation higher than 4QAM.
Keywords
least squares approximations; linear systems; maximum likelihood detection; vectors; QAM; conventional sphere decoding algorithms; maximum likelihood detection problem; partial regularisation approach; signal detection problem; transmit vector; underdetermined integer least squares; underdetermined linear systems;
fLanguage
English
Journal_Title
Communications, IET
Publisher
iet
ISSN
1751-8628
Type
jour
DOI
10.1049/iet-com:20080210
Filename
4745852
Link To Document