12 papers
Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty
Wenlihan Lu, Tianshun Li, Liuqing Yang +1
Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from the target can provide dire…
Uncertainty-Guided UAV Spectrum Cartography with Deep-Unfolded Online Tensor Decomposition
Shangjie Zhuang, Jiahui Liang, Shijian Gao
Spectrum cartography is crucial for spectrum-aware resource management in low-altitude networks, where uncrewed aerial vehicles (UAVs) collect spectrum measurements to reconstruct…
Sensing While Communicating: Active Online Spectrum Cartography via Air-Ground Cooperation
Shangjie Zhuang, Jiahui Liang, Shijian Gao
Spectrum cartography is crucial for spectrum-aware resource management in low-altitude networks, where uncrewed aerial vehicles (UAVs) collect measurements to reconstruct power spe…
Active Perception for Radio Map Reconstruction in Uncharted 3D Air-Ground Environments
Wenlihan Lu, Miaowen Wen, Shijian Gao
Radio maps provide the essential foundation for low altitude networking systems. Unlike terrestrial radio maps that are typically generated via drive test measurements, mapping the…
Learn to Access and Backhaul the Sky: Multi-Scale Radio Map Guided Multi-UAV Cooperation
Yifeng Yuan, Shijian Gao
Driven by the emerging low-altitude economy, uncrewed aerial vehicle (UAV) swarms offer flexible integrated air-ground access and backhaul. However, providing seamless connectivity…
Dynamic Task and Resource Scheduling Towards Green Space-Air-Ground-Sea Integrated Network
Yufei Ye, Shijian Gao, Xinhu Zheng +1
In the context of 6G ubiquitous connectivity, the space-air-ground-sea integrated network (SAGSIN) emerges as a new paradigm to provide critical services for resource-limited ocean…
TeRFS: Temporal-Evolving Radio Field Synthesis
Pengyang Zhang, Wenlihan Lu, Shijian Gao
While radio-frequency (RF) field synthesis is fundamental to wireless networking, current approaches remain constrained by static assumptions, leaving them unable to track the rapi…
Scalable Multimodal Beam Alignment in V2X: An Anti-Imbalance Graph Learning Approach
Jiahui Liang, Shuoyao Wang, Shijian Gao
Efficient beam alignment is fundamental to high-throughput and reliable connectivity in Vehicle-to-Everything (V2X) systems. However, conventional beam management in dynamic vehicu…
Transfer to Sky: Unveil Low-Altitude Route-Level Radio Maps via Ground Crowdsourced Data
Wenlihan Lu, Huacong Chen, Ruiyang Duan +2
The expansion of the low-altitude economy is contingent on reliable cellular connectivity for unmanned aerial vehicles (UAVs). A key challenge in pre-flight planning is predicting…
Relaying Signal When Monitoring Traffic: Double Use of Aerial Vehicles Towards Intelligent Low-Altitude Networking
Jiahui Liang, Wenlihan Lu, Tianyi Liu +5
In intelligent low-altitude networks, integrating monitoring tasks into communication unmanned aerial vehicles (UAVs) can consume resources and increase handoff latency for communi…
Bayesian-Driven Graph Reasoning for Active Radio Map Construction
Wenlihan Lu, Shijian Gao, Miaowen Wen +4
With the emergence of the low-altitude economy, radio maps have become essential for ensuring reliable wireless connectivity to aerial platforms. Autonomous aerial agents are commo…
Aligning Beam with Imbalanced Multi-modality: A Generative Federated Learning Approach
Jiahui Liang, Miaowen Wen, Shuoyao Wang +2
As vehicle intelligence advances, multi-modal sensing-aided communication emerges as a key enabler for reliable Vehicle-to-Everything (V2X) connectivity through precise environment…