DocumentCode
1090161
Title
Maximum likelihood receivers for space-time coded MIMO systems with gaussian estimation errors
Author
Chen, Yunfei ; Beaulieu, Norman C.
Author_Institution
Sch. of Eng., Univ. of Warwick, Coventry
Volume
57
Issue
6
fYear
2009
fDate
6/1/2009 12:00:00 AM
Firstpage
1712
Lastpage
1720
Abstract
Maximum likelihood (ML) receivers for space-time coded multiple-input multiple-output (MIMO) systems with Gaussian channel estimation errors are proposed. Two different cases are considered. In the first case, the conditional probability density function (PDF) of the channel estimate is assumed Gaussian and known. In the second case, the joint PDF of the channel estimate and the true channel gain is assumed Gaussian and known. In addition to ML signal detection for space-time coded MIMO with ML and minimum mean-squared-error channel estimation, ML signal detection without channel estimation is also studied. Two suboptimal structures are derived. The Alamouti space-time codes are used to examine the performances of the new receivers. Simulation results show that the new receivers can reduce the gap between the conventional receiver with channel estimation errors and the receiver with perfect channel knowledge at least by half in some cases.
Keywords
MIMO communication; channel estimation; maximum likelihood detection; mean square error methods; radio receivers; space-time codes; Alamouti space-time codes; Gaussian channel estimation errors; MIMO systems; maximum likelihood receivers; maximum likelihood signal detection; mean squared error; perfect channel knowledge; probability density function; Channel estimation; Error analysis; Estimation error; Gaussian channels; MIMO; Maximum likelihood detection; Maximum likelihood estimation; Probability density function; Signal detection; Space time codes; Channel estimation, imperfect, maximum likelihood, MIMO.;
fLanguage
English
Journal_Title
Communications, IEEE Transactions on
Publisher
ieee
ISSN
0090-6778
Type
jour
DOI
10.1109/TCOMM.2009.06.070241
Filename
5089510
Link To Document