Active Sensing-assisted UAV Communications with Jittering: Framework and Performance Analysis

2026-06-11

AI Summary

This work addresses the severe degradation in communication reliability between low-altitude unmanned aerial vehicles (UAVs) and terrestrial cellular networks caused by airframe jitter-induced beam misalignment. To mitigate this issue, the authors propose a two-stage active sensing–assisted communication framework, which, for the first time, integrates active sensing into jitter compensation. Two distinct strategies—communication-oriented and sensing-oriented—are designed, and their fundamental trade-off in time-slot allocation is analytically revealed. Leveraging maximum likelihood angle estimation, Cramér–Rao bound analysis, and joint design of Gaussian information signals with deterministic sensing waveforms, closed-form expressions for the achievable rates of both schemes are derived, along with semi-closed-form optimal time-slot allocations. Theoretical and simulation results demonstrate that performance loss vanishes at high transmit power, and the communication-oriented scheme significantly outperforms the sensing-oriented counterpart under a specific threshold condition.

Abstract

Providing reliable communication for unmanned aerial vehicles (UAVs) via existing cellular networks is crucial for enabling the rapid growth of the low-altitude economy. However, UAV jittering significantly degrades communication quality due to induced beam misalignment. Inspired by recent advances in integrated sensing and communication, we propose a novel two-stage active sensing-assisted communication framework tailored for ground-to-UAV links with jittering. Specifically, two schemes are conceived to leverage sensing for enhancing communication performance, namely the communication-oriented scheme and the sensing-oriented scheme. For the sensing-oriented scheme, deterministic signals are employed in the first stage to facilitate angle-of-arrival (AoA) acquisition at the UAV side, followed by pure communication service in the second stage by using the estimated AoA. In contrast, the communication-oriented scheme employs Gaussian information-bearing signals throughout both stages, with AoA estimation relying on Gaussian random signals. For both schemes, we provide maximum likelihood estimators for AoA, along with analytical results characterizing the Cramér-Rao bound. To capture the performance limit, closed-form expressions for the achievable rates of the two schemes are derived, unveiling a fundamental tradeoff between sensing and communication quality across the two stages by tuning the time allocated to the first stage. The optimal time allocation that maximizes the overall rate is obtained in semi-closed-form. Based on these results, we unveil a sufficient condition under which the communication-oriented scheme outperforms the sensing-oriented scheme, which admits an interesting threshold-based structure. Asymptotic analysis demonstrates that the performance loss of the proposed schemes relative to the jitter-free upper bound approaches zero in the high transmit power regime.

Problem

• UAV communications
• jittering
• beam misalignment
• active sensing
• integrated sensing and communication

Innovation

• active sensing
• UAV communications
• beam misalignment
• integrated sensing and communication
• angle-of-arrival estimation