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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Olama, M.M. Djouadi, S.M. Charalambous, C.D. |
| Copyright Year | 2002 |
| Abstract | Mobile-to-mobile networks are characterized by node mobility that makes the propagation environment time varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) which varies from one observation instant to the next. The current models do not capture and track the time varying characteristics. This paper is concerned with dynamical modeling of time varying mobile-to-mobile channels, parameter estimation and identification from received signal measurements. The evolution of the propagation environment is described by stochastic differential equations, whose parameters can be determined by approximating the band-limited DPSD using the Gauss-Newton method. However, since the DPSD is not available online, we propose to use a filter-based expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively. The scheme results in a finite dimensional filter which only uses the first and second order statistics. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated online from received signal measurements. The algorithms are tested using experimental data collected from moving sensor nodes in indoor and outdoor environments demonstrating the method's viability. |
| File Size | 793393 |
| File Format | |
| ISSN | 15361276 |
| Volume Number | 8 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-04-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic processes Differential equations Communication channels Parameter estimation Recursive estimation Fading Signal processing Time measurement Newton method Least squares methods estimation and identification Mulipath fading channels stochastic differential equations Doppler spectral density Kalman filter expectation maximization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Electrical and Electronic Engineering Computer Science Applications |
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