Title
Time-Varying Channel Estimation Using Two-Dimensional Channel Orthogonalization and Superimposed Training
Abstract
In this correspondence, a method is presented for estimating double-selective channels using superimposed training (ST). The estimator is based on a subspace projection of the time-varying channel onto a set of two dimensional orthogonal functions. These functions are formed via the outer product of the discrete prolate spheroidal basis vectors and the universal basis vectors. This approach allows the channel to be expanded in both the time-delay and time dimensions with the fewest parameters when incomplete channel statistics are given. This correspondence also provides a theoretical performance analysis of the estimation algorithm and its corroboration via simulations. It is shown that this new method provides an enhancement in channel estimation when compared with state-of-the-art approaches.
Year
DOI
Venue
2012
10.1109/TSP.2012.2195658
IEEE Transactions on Signal Processing
Keywords
Field
DocType
vectors
Outer product,Mathematical optimization,Orthogonal functions,Subspace topology,Communication channel,Basis (linear algebra),Orthogonalization,Multiple time dimensions,Mathematics,Estimator
Journal
Volume
Issue
ISSN
60
8
1053-587X
Citations 
PageRank 
References 
9
0.54
7
Authors
7