Joint Beamwidth and Power Density Allocation for ISAC-Enabled AAVs in Low-Altitude Economy

This paper investigates integrated sensing and communication (ISAC) in low-altitude economy (LAE) networks, which is crucial for the flight safety of low-altitude unmanned aerial vehicles (UAVs). We derive the expected achievable rate (EAR) as a novel performance metric to evaluate the ISAC system performance under uncertain predicted direction. Both accurate beam direction prediction and beam resource allocation are essential for achieving fair EAR performance for multiple UAVs. However, the trajectories of the UAVs exhibit non-Gaussian deviations from the predefined trajectories. Moreover, the beamwidth and power density are interdependent for EAR performance. Motivated by this, we propose a transformer-based multitype weighting network (TMW-Net) to obtain accurate UAV state prediction under non-Gaussian scenarios. Building upon the state prediction results, we develop a joint beamwidth and power density allocation (JBPDA) method to maximize the minimum EAR for multiple UAVs. The proposed method searches for an auxiliary variable by establishing a power consumption-based feasibility evaluation problem, which is transformed into a simpler form through the cases of symmetric and asymmetric beam allocation. Finally, the numerical results show that the proposed TMW-Net has higher beam direction prediction accuracy. Furthermore, the designed JBPDA method can achieve a trade-off between communication and sensing in the ISAC system.