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UKF Prediction Assisted UAV Sensing and Communication Optimization Design for Air-Ground Networks

Qingyin Chang, Zhicheng Dong*

Abstract


This paper studies the joint design of sensing and communication in air-ground networks, where multiple unmanned aerial vehicles
(UAVs) cooperate to assist the base station in sensing and serving mobile users. To improve the sensing accuracy, we propose an unbiased
Kalman filter (UKF) based UAV sensing scheme. The performance of communication and sensing is characterized by the downlink communication rate and the Cramer-Rao lower bound (CRLB) of the user location estimation, respectively. To maximize the downlink communication rate while accurately tracking the user’s location, this involves solving the user association and UAV trajectory optimization problems.
In particular, we formulate the joint optimization problem as a mixed integer non-convex optimization problem, which is difficult to solve.
To address this problem, we first derive the CRLB in a closed form based on the user’s state prediction. Then, the original problem is decomposed into two sub-problems, one corresponding to the optimization of user association and the other one about the optimization of UAV
trajectory. An iterative algorithm is introduced to optimize the two sub-problems alternately using a relaxation-based method and a continuous convex approximation method. Comparisons with existing algorithms verify that our designed scheme can achieve superior performance
improvements in user tracking and communication.

Keywords


UAV Sensing; Communication Optimization; Air-Ground Networks; Unbiased Kalman Filter (UKF); Mixed Integer Non-Convex Optimization

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References


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DOI: https://doi.org/10.18686/utc.v10i3.242

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Copyright (c) 2024 Qingyin Chang,Zhicheng Dong*