Problem
Research questions and friction points this paper is trying to address.
drone trajectory tracking
low-altitude wireless networks
sensing errors
wireless link reliability
flight safety
Closed-Loop Integrated Sensing, Communication, and Control for Efficient Drone Flight
🤖 AI Summary
This work addresses the challenge of trajectory deviation in low-altitude wireless networks, where complex channel conditions and limited spectral and power resources induce sensing errors and unreliable communications. To mitigate these issues, the paper proposes an integrated perception-communication-control closed-loop framework for UAV trajectory tracking. For the first time, it jointly models finite-blocklength communication, sensing inaccuracies, and control command packet loss under explicit stability constraints, and derives a theoretical lower bound on control resources required to guarantee system stability. Through rigorous stability analysis, joint time-frequency resource optimization, and a successive convex approximation algorithm, the approach achieves decimeter-level average tracking accuracy while ensuring stability—reducing trajectory error to merely 17.37% of that incurred by conventional GNSS-based methods and effectively suppressing trajectory divergence caused by finite-blocklength transmissions.
📝 Abstract
Low-altitude wireless networks (LAWN) require drones to follow specific trajectories controlled by ground base stations (GBSs). However, given complex low-altitude channel conditions and limited spectrum and power resources, sensing errors and wireless link unreliability cannot be ignored, leading to trajectory deviations that threaten flight safety. To address this issue, this paper proposes an integrated sensing-communication-control (ISCC) closed-loop trajectory tracking approach, aiming to reveal the coupling mechanisms among communication, sensing, and control during drone flight. In detail, we incorporate sensing errors in trajectory state estimation, packet losses in control command transmission, and finite blocklength transmission effects into the closed-loop dynamics. First, through theoretical analysis, we identify the dominant role of the time-frequency resources allocated to control in ensuring system stability and derive a lower bound on the resources required to guarantee stable operation. Second, to minimize tracking error, we formulate a time-frequency resource allocation optimization problem for the sensing, communication, and control components, subject to constraints on communication rate and closed-loop stability. Accordingly, a solution algorithm based on successive convex approximation is proposed. Third, simulation results indicate that once stability is ensured, system performance is primarily determined by sensing accuracy, with the trajectory tracking error exhibiting an approximately linear dependence on the position error bound. Finally, it is shown that the proposed ISCC scheme avoids trajectory divergence under FBL transmission compared with ISCC designs ignoring control packet loss, and could achieve decimeter-level average tracking accuracy, reducing the error to only 17.37% of that observed in the baseline global navigation satellite system scheme.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Integrated Sensing-Communication-Control (ISCC)
Closed-loop trajectory tracking
Finite Blocklength (FBL) communication
Time-frequency resource allocation
Drone flight stability
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