Chao Yang, Junfeng Wu, Wei Zhang, Ling Shi
EXTENDED ABSTRACT. Networked sensing, estimation, and control systems have attracted much attention over the past decade [1], thanks to the recent advances in sensor and communication technology. Remote state estimation and information processing have a wide range of applications such as in environmental monitoring, body sensor network, vehicle navigation, industrial process, smart grid, etc. In many of the aforementioned applications, sensors that collect physical data of interest may be
more » ... terest may be battery-powered, which means that the energy for the sensors to communicate with each other is limited. Network bandwidth is often a scarce resource and could be limited as well. Therefore, a sensor may not be able to communicate with its neighbors at each time. These practical constraints require an appropriate communication scheduling algorithm to balance the limited communication resource and the performance of the state estimation [2, 3, 5]. In this paper, we consider the following discrete linear time-invariant process x k+1 = Ax k + w k .