UAV-Enabled ISAC: Towards On-Demand Sensing Services and Enhanced Communication

In this paper, we investigate an integrated sensing-and-communication (ISAC) network enabled by an unmanned aerial vehicle (UAV). The UAV is supposed to fly along a periodical circular trajectory at a fixed height for ISAC service supply from the sky. We consider on-demand sensing services, where on-demand detection and on-demand localization requests may be activated at any time toward any position within the targeted serving region. While guaranteeing satisfactory accuracy for both on-demand sensing tasks, we aim at maximizing the minimum achievable throughput among all communication users, via joint optimizing the UAV trajectory and communication user scheduling. To address the complicated problem with infinite sensing constraints, we characterize the on-demand detection constraint as a restricted deployment area for UAV and the on-demand localization constraint as Cramer-Rao Bound (CRB) constraints over finite reference target points, based on which the original problem is simplified to more tractable one. Afterwards, particularly aiming to ensure no violations of CRB constraints, we propose a convex approximation for the reformulated problem, where tight approximation is guaranteed at given local solution. The construction strategy for convex problem approximation allows an efficient iterative algorithm with verified convergence to a superior suboptimal solution. At last, with simulations, we verified the applicability of our developed optimization scheme in strictly fulfilling the on-demand sensing constraints and the effectiveness of our proposed solution for simultaneously enhancing the communication throughput in UAV-enabled ISAC.

💡 Research Summary

This paper investigates an integrated sensing‑and‑communication (ISAC) network in which a single unmanned aerial vehicle (UAV) flies at a fixed altitude along a periodic circular trajectory and simultaneously serves multiple ground communication users while providing on‑demand sensing services. The sensing services consist of two types of requests that may appear at any time and at any location within a predefined service region: (i) target detection and (ii) target localization. The authors aim to guarantee a prescribed quality‑of‑service (QoS) for both sensing tasks and, under these constraints, maximize the minimum achievable throughput among all communication users by jointly optimizing the UAV’s trajectory and the user‑scheduling variables.

System model. The operation period (T) is divided into (N) equal time slots of duration (\delta = T/N). The UAV position in slot (n) is ((x_n, y_n)) (altitude (H) is fixed). A speed limit (V) yields the motion constraint ((x_{n+1}-x_n)^2+(y_{n+1}-y_n)^2 \le (\delta V)^2) and the circular trajectory is enforced by the same constraint between slot (N) and slot (1). For the communication link, a free‑space path‑loss model is adopted; the channel capacity to user (k) in slot (n) is
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