TY - GEN
T1 - SAULC
T2 - 3rd International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2025
AU - Qin, Liangwei
AU - Li, Dongbo
AU - Li, Chongrong
AU - Hou, Yibo
AU - Gao, Jiahe
AU - Yin, Bo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - The collaboration between Unmanned Aerial Vehicles (UAVs) and Low Earth Orbit (LEO) satellites represents an emerging edge computing paradigm that holds significant potential for enabling ubiquitous connectivity in the Internet of Things (IoT). However, highly dynamic UAV-satellite links lead to high Doppler shift, high path loss, and other issues, which cause serious semantic distortion. Meanwhile, LEO satellite spectrum resources are extremely limited. Thus, realizing end-to-end reliable UAV-LEO satellite communications with lower communication bandwidth in poor channel environments presents a significant challenge. To address these challenges, this paper proposes the Semantics-driven Adaptive UAV-LEO Satellite Cooperative Communication System (SAULC), establishing the first UAV-LEO satellite semantic communication architecture. The system systematically incorporates time-varying channel characteristics, including Doppler shift, path loss, and atmospheric attenuation, while employing a low-complexity Flatten Transformer architecture with integrated channel feedback mechanisms. Experiments show that the proposed model significantly outperforms conventional schemes under time-varying UAV-satellite channels.
AB - The collaboration between Unmanned Aerial Vehicles (UAVs) and Low Earth Orbit (LEO) satellites represents an emerging edge computing paradigm that holds significant potential for enabling ubiquitous connectivity in the Internet of Things (IoT). However, highly dynamic UAV-satellite links lead to high Doppler shift, high path loss, and other issues, which cause serious semantic distortion. Meanwhile, LEO satellite spectrum resources are extremely limited. Thus, realizing end-to-end reliable UAV-LEO satellite communications with lower communication bandwidth in poor channel environments presents a significant challenge. To address these challenges, this paper proposes the Semantics-driven Adaptive UAV-LEO Satellite Cooperative Communication System (SAULC), establishing the first UAV-LEO satellite semantic communication architecture. The system systematically incorporates time-varying channel characteristics, including Doppler shift, path loss, and atmospheric attenuation, while employing a low-complexity Flatten Transformer architecture with integrated channel feedback mechanisms. Experiments show that the proposed model significantly outperforms conventional schemes under time-varying UAV-satellite channels.
KW - Edge computing
KW - Semantic communication
KW - Time-varying channels
KW - UAV-LEO collaboration
UR - https://www.scopus.com/pages/publications/105028089863
U2 - 10.1007/978-981-95-2581-2_15
DO - 10.1007/978-981-95-2581-2_15
M3 - 会议稿件
AN - SCOPUS:105028089863
SN - 9789819525805
T3 - Communications in Computer and Information Science
SP - 224
EP - 237
BT - Artificial Intelligence of Things and Systems - 3rd International Conference, AIoTSys 2025, Proceedings
A2 - Liu, Sicong
A2 - Zheng, Xiaolong
A2 - Ma, Dong
A2 - Wu, Yuezhong
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 15 August 2025 through 17 August 2025
ER -