Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

This letter presents a sensing-communication computing-control (SC3) integrated satellite unmanned aerial vehicle (UAV) network, where UAVs are equipped with sensors, mobile edge computing (MEC) servers, base stations and satellite communication modules. Like a nervous system, this integrated network is capable of organizing multiple field robots in remote areas, so as to perform mission-critical tasks which are dangerous for humans. Aiming at activating this nervous system with multiple SC3 loops, we present a control-oriented optimization problem. Different from traditional studies which mainly focused on communication metrics, we address the power allocation issue to minimize the sum linear quadratic regulator (LQR) control cost of all SC3 loops. Specifically, we show the convexity of the problem and reveal the relationship between the optimal transmit power and intrinsic entropy rates of different SC3 loops. For the assure-to-be-stable case, we derive a closed-form solution for ease of practical applications. After demonstrating the superiority of the control-oriented power allocation, we further highlight its difference from the classic capacity-oriented water-filling method.