Stochastic power control for time-varying long-term fading wireless networks
EURASIP Journal on Applied Signal Processing
Recursive estimation and identification of time-varying long-term fading channel
Research Letters in Signal Processing
Recursive estimation and identification of wireless ad hoc channels from measurements
WICON '07 Proceedings of the 3rd international conference on Wireless internet
Optimal parameter trajectory estimation in parameterized SDEs: An algorithmic procedure
ACM Transactions on Modeling and Computer Simulation (TOMACS)
IEEE Transactions on Wireless Communications
Stochastic UWB wireless channel modeling and estimation from received signal measurements
RWS'09 Proceedings of the 4th international conference on Radio and wireless symposium
CA '07 Proceedings of the Ninth IASTED International Conference on Control and Applications
On Kalman filtering over fading wireless channels with controlled transmission powers
Automatica (Journal of IFAC)
| Hi-index | 754.84 |
The power control of wireless networks is formulated using a stochastic optimal control framework, in which the evolution of the channel is described by stochastic differential equations (SDEs). The latter capture the spatio-temporal variations of the communication link, as well as the randomness. This class of models is more realistic than the static models usually encountered in the literature. Under this scenario, average and probabilistic Quality of Service (QoS) measures are introduced to evaluate the performance of any control strategy by using Chernoff bounds. Moreover, the Chernoff bound is computed explicitly, while the solution of the stochastic optimal power control is obtained through pathwise optimization. The pathwise optimization can be solved using linear programming if predictable control strategies are introduced. Finally, if predictable control strategies do not hold, it is shown that the proposed power control problem reduces to particular convex optimizations.