Age of Information Minimization in UAV-Enabled Integrated Sensing and Communication Systems
Rattachement africain : cn, fi, us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Unmanned aerial vehicles (UAVs) equipped with integrated sensing and communication (ISAC) capabilities are envisioned to play a pivotal role in future wireless networks due to their enhanced flexibility and efficiency. However, jointly optimizing UAV trajectory planning, multi-user communication, and target sensing under stringent resource constraints and time-critical conditions remains a significant challenge. To address this, we propose an Age of Information (AoI)-centric UAV-ISAC system that simultaneously performs target sensing and serves multiple ground users, emphasizing information freshness as the core performance metric. We formulate a long-term average AoI minimization problem that jointly optimizes the UAV's flight trajectory and beamforming. To tackle the high-dimensional, non-convexity of this problem, we develop a deep reinforcement learning (DRL)-based algorithm capable of providing real-time decisions on UAV movement and beamforming for both radar sensing and multi-user communication. Specifically, a Kalman filter is employed for accurate target state prediction, regularized zero-forcing is utilized to mitigate inter-user interference, and the Soft Actor-Critic algorithm is applied for training the DRL agent on continuous actions. The proposed framework adaptively balances the trade-offs between sensing accuracy and communication quality. Extensive simulation results demonstrate that our proposed method consistently achieves lower average AoI compared to baseline approaches.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Age of Information Minimization in UAV-Enabled Integrated Sensing and Communication Systems
- Date Crossref
- 01/01/2026
- Éditeur
- Institute of Electrical and Electronics Engineers (IEEE)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Taiyuan University of Technology pays non établi dans la noticeUniversité ou école supérieure
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University of Electronic Science and Technology of China pays non établi dans la noticeUniversité ou école supérieure
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Aalto University Department of Information and Communications Engineering pays non établi dans la noticeUniversité ou école supérieure
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University of Houston Department of Electrical and Computer Engineering pays non établi dans la noticeUniversité ou école supérieure
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School of Software pays non établi dans la noticeUniversité ou école supérieure
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School of Computer Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
Taiyuan University of Technology, University of Electronic Science and Technology of China et Department of Information and Communications Engineering — Aalto University, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.