@inproceedings{683cd4155b6f415d9a5facf75ae2ebbb,
title = "Semi-blind subspace techniques for digital communication systems",
abstract = "This paper is devoted to the analysis of a {"}semi-blind{"} estimation framework in which the standard input-output (training sequence based) estimation is enhanced by using the statistical structure of the information sequence. More specifically, we consider the case of a general TDMA frame-based receiver equipped with multiple sensors, and restrict our attention to second-order based subspace methods which are suitable for most standard communication applications due to their moderate computational cost. The channel estimator is obtained as a regularized least-squares solution where the blind subspace criterion plays the role of the regularization constraint. The main contribution of the paper consists in showing by asymptotic analysis how to optimally tune the balance between the blind criterion and the least-squares fit depending on the design parameters of the system. Simulations show that the proposed solutions are very effective and significantly improve the efficiency of the equalization.",
keywords = "Array processing, Channel equalization, Semi-blind estimation, Subspace techniques",
author = "Vincent Buchoux and Eric Moulines and Olivier Capp{\'e} and Alexei Gorokhov",
note = "Publisher Copyright: {\textcopyright} 1999 IEEE.; 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC 1999 ; Conference date: 09-05-1999 Through 12-05-1999",
year = "1999",
month = jan,
day = "1",
doi = "10.1109/SPAWC.1999.783018",
language = "English",
series = "IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "58--61",
booktitle = "1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC 1999",
}