NDLI: Bilinear approach to multiuser second-order statistics-based blind channel estimation

Content Provider	IEEE Xplore Digital Library
Author	Krauss, T.P. Zoltowski, R.D.
Copyright Year	1991
Abstract	We present a bilinear approach to multiple-input multiple-output (MIMO) blind channel estimation where products of the channel parameters are first estimated from the covariance of the received data. The channel parameters are then obtained as the dominant eigenvectors of the outer-product estimate. Necessary and sufficient identifiability conditions are presented for a single channel and extended to the multichannel case. It is found that this technique can identify the channel to within a subspace ambiguity, as long as the basis functions for the channel satisfy certain constraints, regardless of the left invertability of the channel matrix. One important requirement for identifiability is that the number of channel parameters is small compared with the channel length; advantageously, this is exactly the situation in which this algorithm has significantly lower complexity than competing (parametric, multiuser) blind algorithms. Simulations show that the technique is applicable in situations where typical identifiability conditions fail: common nulls, a single symbol-spaced channel, and more users than channels. These simulations are for the "almost flat" faded situation when the propagation delay spread is a fraction of the transmission pulse duration (as might be found in current TDMA systems). Comparisons are made, when possible, to a subspace method incorporating knowledge of the basis functions. The bilinear approach requires significantly less computation but performs better than the subspace method at low SNR, especially for multiple users.
Sponsorship	IEEE Signal Processing Society
Starting Page	2473
Ending Page	2486
Page Count	14
File Size	348689
File Format	PDF
ISSN	1053587X
Volume Number	48
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blind equalizers Signal processing algorithms Matrix decomposition Parameter estimation Digital communication Multipath channels Vectors MIMO Subspace constraints Computational modeling
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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