3 papers
cs.DC2025
Split Federated Learning Empowered Vehicular Edge Intelligence: Concept, Adaptive Design and Future Directions
Xianke Qiang, Zheng Chang, Chaoxiong Ye +2
To achieve ubiquitous intelligence in future vehicular networks, artificial intelligence (AI) is essential for extracting valuable insights from vehicular data to enhance AI-driven…
cs.LG2024
Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
Xianke Qiang, Zheng Chang, Yun Hu +2
Vehicular edge intelligence (VEI) is a promising paradigm for enabling future intelligent transportation systems by accommodating artificial intelligence (AI) at the vehicular edge…
cs.NI2024
Enhanced Physical Layer Security for Full-duplex Symbiotic Radio with AN Generation and Forward Noise Suppression
Chi Jin, Zheng Chang, Fengye Hu +2
Due to the constraints on power supply and limited encryption capability, data security based on physical layer security (PLS) techniques in backscatter communications has attracte…