Research on Integrated Sensing and Communication Technology of Unmanned Aerial Vehicles

In response to the demands of 6G space-air-ground integrated networks and the development of low-altitude economy, the integrated sensing and communication (ISAC) technology for unmanned aerial vehicles (UAVs) has emerged as a novel core solution that combines wireless transmission and sensing functions. With the advantages of strong mobility and flexible deployment, UAV swarms combined with ISAC, can significantly enhance system performance. However, the ISAC for UAV swarms still faces three major challenges: difficult physical layer transmission design, difficult cooperative networking, and difficult joint scheduling of multiple tasks. To address these challenges, this paper proposes key technologies such as deep reinforcement learning, multi-sensor fusion, and parameter estimation, focusing on breakthroughs in transmission design, cooperative networking, and joint optimization of communication and sensing resources for ISAC for UAV swarms, promoting theoretical innovation and system implementation for low-altitude economy applications in the 6G era.

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Publication Details

Journal
Computer Simulation in Application
Published
2025-03-26
DOI
https://doi.org/10.18063/csa.v3i1.915
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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Research on Integrated Sensing and Communication Technology of Unmanned Aerial Vehicles

Jianwei Zhao, Fenggan Zhang, Nuo Chen, Nan Jiang et al.
Computer Simulation in Application
UAV Applications and Optimization
article

Research on Integrated Sensing and Communication Technology of Unmanned Aerial Vehicles

Jianwei Zhao, Fenggan Zhang, Nuo Chen, Nan Jiang, Fang He, Weimin Jia
article en

Abstract

In response to the demands of 6G space-air-ground integrated networks and the development of low-altitude economy, the integrated sensing and communication (ISAC) technology for unmanned aerial vehicles (UAVs) has emerged as a novel core solution that combines wireless transmission and sensing functions. With the advantages of strong mobility and flexible deployment, UAV swarms combined with ISAC, can significantly enhance system performance. However, the ISAC for UAV swarms still faces three major challenges: difficult physical layer transmission design, difficult cooperative networking, and difficult joint scheduling of multiple tasks. To address these challenges, this paper proposes key technologies such as deep reinforcement learning, multi-sensor fusion, and parameter estimation, focusing on breakthroughs in transmission design, cooperative networking, and joint optimization of communication and sensing resources for ISAC for UAV swarms, promoting theoretical innovation and system implementation for low-altitude economy applications in the 6G era.

Computer Simulation in ApplicationVol. 3(1)
PLA Rocket Force University of Engineering (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
UAV Applications and Optimization
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