Linear stochastic systems
Linear system theory (2nd ed.)
Linear system theory (2nd ed.)
Effects of wireless physical layer modeling in mobile ad hoc networks
MobiHoc '01 Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Microwave Mobile Communications
Microwave Mobile Communications
Stochastic power control for time-varying long-term fading wireless networks
EURASIP Journal on Applied Signal Processing
Autoregressive modeling for fading channel simulation
IEEE Transactions on Wireless Communications
Stochastic power control for wireless networks via SDEs: probabilistic QoS measures
IEEE Transactions on Information Theory
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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.