Power control for multi-sensor remote state estimation over interference channel

Abstract

In this paper, we investigate a multi-sensor transmission power control problem for remote state estimation over interference channel. There are N sensors measuring a dynamic process at the same time and the sensors send their measurements to a remote state estimator for data fusion through a shared packet-dropping channel, where the packet drop rate is related to their transmission power. Traditionally, the transmission power design problem does not consider the situation where the communication process of each sensor may be affected by the interference power from other sensors. To address this issue, we consider a signal-to-interference-and-noise-ratio (SINR)-based channel model to describe the simultaneous transmission process and formulate such a power control problem into a stochastic programming problem. A certainty-equivalent problem is proposed to tackle the difficulties brought by the implicit expression of the objective function and the non-linearity/non-convexity of the original problem. By utilizing an approximated SINR quantity, a sub-optimal solution to the optimal power control problem is also obtained by solving a standard convex optimization problem. An event-based power controller, a heuristic power controller, and the power control problem with a threshold-based channel model are also discussed. Performance analysis of the sub-optimal controller and the comparison with other power controllers are demonstrated to show the effectiveness of our methods.