UAV-Assisted Communications in SAGIN-ISAC: Mobile User Tracking and Robust Beamforming

Both the space-air-ground integrated networks (SAGIN) and the integrated sensing and communication (ISAC) are promising technologies in future communication systems. This paper investigates the mobile user (MU) tracking and robust beamforming design by the unmanned aerial vehicle (UAV) in an SAGIN-ISAC system. Two schemes for acquiring the location information of MUs at the UAV are proposed, namely the space-assisted and ISAC-assisted schemes. The former requires the precise location information from the satellite by the space-air transmission, while the latter estimates the location information of MUs via a proposed extended Kalman filter based algorithm. The obtained location information is then utilized to predict the channel distribution of MUs, which can be used to formulate an outage-constrained energy efficiency (EE) maximization problem. The considered problem is first reformulated based on the Bernstein-type inequality to derive computationally tractable forms of the outage probability constraints. Then, the reformulated problem is solved via the semi-definite relaxation (SDR) and successive convex approximation methods, where the tightness of employing SDR is theoretically proved. Numerical results illustrate the trajectories of the UAV for tracking MUs under the space-assisted and ISAC-assisted schemes, and discuss the impact of the space-air transmission on the EE performance. It is observed that there exists a trade-off between space-air transmission overhead and location prediction precision of MUs. By integrating the ISAC in SAGIN, the information demand from the space is reduced compared with traditional SAGIN.