Stochastic wireless channel modeling, estimation and identification from measurements
Date
2008ISBN
978-0-7354-0540-0Source
AIP Conference ProceedingsAIP Conference Proceedings
Volume
1019Pages
433-438Google Scholar check
Keyword(s):
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This paper is concerned with stochastic modeling of wireless fading channels, parameter estimation, and system identification from measurement data. Wireless channels are represented by stochastic state-space form, whose parameters and state variables are estimated using the expectation maximization algorithm and Kalman filtering, respectively. The latter are carried out solely from received signal measurements. These algorithms estimate the channel inphase and quadrature components and identify the channel parameters recursively. The proposed algorithm is tested using measurement data, and the results are presented. © 2008 American Institute of Physics.