DocumentCode :
3257010
Title :
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
Author :
Abuthinien, M. ; Sheng Chen ; Wolfgang, A. ; Hanzo, Lajos
Author_Institution :
Univ. of Southampton, Southampton
fYear :
2007
fDate :
24-28 June 2007
Firstpage :
5354
Lastpage :
5358
Abstract :
Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative two-level optimisation loop. An efficient global optimisation search algorithm called the repeated weighted boosting search is employed at the upper level to identify the unknown MIMO channel model while an enhanced ML sphere detector called the optimised hierarchy reduced search algorithm aided ML detector is used at the lower level to perform the ML detection of the transmitted data. A simulation example is included to demonstrate the effectiveness of these two schemes.
Keywords :
MIMO communication; channel estimation; iterative methods; maximum likelihood detection; maximum likelihood estimation; search problems; MIMO channel model; ML sphere detector; global optimisation search algorithm; iterative two-level optimisation; joint maximum likelihood channel estimation; multiple-input multiple-output systems; repeated weighted boosting search; Bandwidth; Boosting; Channel estimation; Computational complexity; Detectors; Iterative algorithms; MIMO; Maximum likelihood detection; Maximum likelihood estimation; Receiving antennas;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, 2007. ICC '07. IEEE International Conference on
Conference_Location :
Glasgow
Print_ISBN :
1-4244-0353-7
Type :
conf
DOI :
10.1109/ICC.2007.886
Filename :
4289557
Link To Document :
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