Publication: Characterization of Non-Stationary Channels Using Mismatched Wiener Filtering 

Authors:
Ispas, A. ,  Dörpinghaus, M. ,  Ascheid, G. ,  Zemen, T.
Journal:
IEEE Trans. Signal Process.
Volume:
61
Page(s):
274-288
number:
2
Date:
Jan. 2013
DOI:
10.1109/TSP.2012.2223688
Language:
English

Abstract

A common simplification in the statistical treatment of linear time-varying (LTV) wireless channels is the approximation of the channel as a stationary random process inside certain time-frequency regions. We develop a methodology for the determination of local quasi-stationarity (LQS) regions, i.e., local regions in which a channel can be treated as stationary. Contrary to previous results relying on, to some extent, heuristic measures and thresholds, we consider a finite-length Wiener filter as realistic channel estimator and relate the size of LQS regions in time to the degradation of the mean square error (MSE) of the estimate due to outdated and thus mismatched channel statistics. We show that for certain power spectral densities (PSDs) of the channel a simplified but approximate evaluation of the matched MSE based on the assumption of an infinite filtering length yields a lower bound on the actual matched MSE. Moreover, for such PSDs, the actual MSE degradation is upper-bounded and the size of the actual LQS regions is lower-bounded by the approximate evaluation. Using channel measurements, we compare the evolution of the LQS regions based on the actual and the approximate MSE; they show strong similarities.

Download

BibTeX

Copyright © by IEEE
Ispas_2012_TSP.pdf
© 2021 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.