Title
Blind recognition of linear space-time block codes: a likelihood-based approach
Abstract
Blind recognition of communication parameters is a research topic of high importance for both military and civilian communication systems. Numerous studies about carrier frequency estimation, modulation recognition as well as channel identification are available in literature. This paper deals with the blind recognition of the space-time block coding (STBC) scheme used in multiple-input-multiple-output (MIMO) communication systems. Assuming there is perfect synchronization at the receiver side, this paper proposes three maximum-likelihood (ML)-based approaches for STBC classification: the optimal classifier, the second-order statistic (SOS) classifier, and the code parameter (CP) classifier. While the optimal and the SOS approaches require ideal conditions, the CP classifier is well suited for the blind context where the communication parameters are unknown at the receiver side. Our simulations show that this blind classifier is more easily implemented and yields better performance than those available in literature.
Year
DOI
Venue
2010
10.1109/TSP.2009.2036062
IEEE Transactions on Signal Processing
Keywords
Field
DocType
blind classifier,cp classifier,linear space-time block code,communication system,blind context,blind recognition,likelihood-based approach,modulation recognition,optimal classifier,receiver side,civilian communication system,communication parameter,maximum likelihood,signal detection,maximum likelihood estimation,mimo,space time block code,linear space,statistics,frequency modulation,block codes,transmitters
Synchronization,Mathematical optimization,Higher-order statistics,Block code,MIMO,Communications system,Algorithm,Estimation theory,Classifier (linguistics),Statistics,Space–time block code,Mathematics
Journal
Volume
Issue
ISSN
58
3
1053-587X
Citations 
PageRank 
References 
42
1.59
22
Authors
5
Name
Order
Citations
PageRank
V. Choqueuse11439.66
Mélanie Marazin21004.86
Ludovic Collin3463.07
Koffi-Clement Yao4442.98
Gilles Burel5297113.35