A connection between H∞ control and the absolute stabilizability of uncertain systems
Systems & Control Letters
Movement-based location update and selective paging for PCS networks
IEEE/ACM Transactions on Networking (TON)
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Hybrid Dynamical Systems: Controller and Sensor Switching Problems
Hybrid Dynamical Systems: Controller and Sensor Switching Problems
Nonlinear state estimation for uncertain systems with an integralconstraint
IEEE Transactions on Signal Processing
On location management for personal communications networks
IEEE Communications Magazine
Signaling alternatives in a wireless ATM network
IEEE Journal on Selected Areas in Communications
Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks
IEEE Journal on Selected Areas in Communications
Dynamic resource allocation schemes during handoff for mobile multimedia wireless networks
IEEE Journal on Selected Areas in Communications
Adaptive hard handoff algorithms
IEEE Journal on Selected Areas in Communications
An alternative strategy for location tracking
IEEE Journal on Selected Areas in Communications
Speed control and policing in a cellular mobile network: SpeedNet
Computer Communications
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Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.