Treffer: Projection approximation blind equalization for multicarrier CDMA systems with receiver diversity

Title:
Projection approximation blind equalization for multicarrier CDMA systems with receiver diversity
Source:
Selected Papers from the Conference 'European Wireless 2002'European transactions on telecommunications. 14(1):37-48
Publisher Information:
Chichester: Wiley, 2003.
Publication Year:
2003
Physical Description:
print, 11 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Electrical Engineering, University of California, Los Angeles, United States
ISSN:
1124-318X
Rights:
Copyright 2003 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.14746552
Database:
PASCAL Archive

Weitere Informationen

In this paper we present a new set of blind equalization algorithms for multicarrier CDMA systems with receiver diversity. We first re-examine the cost function in the well-known subspace method and interpret it in terms of the noise projector, which can be effectively approximated by a special weighted spectral decomposition of the data autocorrelation matrix. By adding a user-specific cost term to the common cost function, we show that all user channel responses can be estimated in parallel. A block algorithm with lower complexity is derived first, followed by a recursive algorithm using RLS-type matrix updating. Our new approach treats additional antennas in the same way as a higher processing gain and provides a programmable structure to compromise between spectral and spatial diversity. Simulations show our method is near-far resistant, and our adaptive algorithm has fast convergence.