This letter presents a sensing-communication-computing-control (SC3) integrated satellite unmanned aerial vehicle (UAV) network, where the UAV is equipped with on-board sensors, mobile edge computing (MEC) servers, base stations and satellite communication module. Like the 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 human. 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 formulated problem and reveal the relationship between optimal transmit power and intrinsic entropy rate 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 with classic capacity-oriented water-filling method.
@article{arxiv.2208.14677,
title = {Control-Oriented Power Allocation for Integrated Satellite-UAV Networks},
author = {Chengleyang Lei and Wei Feng and Jue Wang and Shi Jin and Ning Ge},
journal= {arXiv preprint arXiv:2208.14677},
year = {2022}
}