5 papers
GELATO: Generative Entropy- and Lyapunov-based Adaptive Token Offloading for Device-Edge Speculative LLM Inference
Zengzipeng Tang, Yuxuan Sun, Wei Chen +2
The recent growth of on-device Large Language Model (LLM) inference has driven significant interest in device-edge collaborative LLM inference. As a promising architecture, Specula…
Hierarchical Online-Scheduling for Energy-Efficient Split Inference with Progressive Transmission
Zengzipeng Tang, Yuxuan Sun, Wei Chen +3
Device-edge collaborative inference with Deep Neural Networks (DNNs) faces fundamental trade-offs among accuracy, latency and energy consumption. Current scheduling exhibits two dr…
Terahertz Signal Coverage Enhancement in Hall Scenarios Based on Single-Hop and Dual-Hop Reconfigurable Intelligent Surfaces
Ben Chen, Zhangdui Zhong, Ke Guan +4
Terahertz (THz) communication offers ultra-high data rates and has emerged as a promising technology for future wireless networks. However, the inherently high free-space path loss…
Measurement-Based Non-Stationary Markov Tapped Delay Line Channel Model for 5G-Railways
Xuejian Zhang, Ruisi He, Mi Yang +7
5G for Railways (5G-R) is globally recognized as a promising next-generation railway communication system designed to meet increasing demands. Channel modeling serves as foundation…
Cluster-Based Time-Variant Channel Characterization and Modeling for 5G-Railways
Xuejian Zhang, Ruisi He, Bo Ai +6
With the development of high-speed railways, 5G for Railways (5G-R) is gradually replacing Global System for the Mobile Communications for Railway (GSM-R) worldwide to meet increas…