6 papers
Large Language Models for Wireless Communications: From Adaptation to Autonomy
Le Liang, Hao Ye, Yucheng Sheng +4
The emergence of large language models (LLMs) has revolutionized artificial intelligence, offering unprecedented capabilities in reasoning, generalization, and zero-shot learning.…
A Wireless Foundation Model for Multi-Task Prediction
Yucheng Sheng, Jiacheng Wang, Xingyu Zhou +4
With the growing complexity and dynamics of the mobile communication networks, accurately predicting key system parameters, such as channel state information (CSI), user location,…
SComCP: Task-Oriented Semantic Communication for Collaborative Perception
Jipeng Gan, Yucheng Sheng, Hua Zhang +4
Reliable detection of surrounding objects is critical for the safe operation of connected automated vehicles (CAVs). However, inherent limitations such as the restricted perception…
Task-Oriented Semantic Communication for Stereo-Vision 3D Object Detection
Zijian Cao, Hua Zhang, Le Liang +3
With the development of computer vision, 3D object detection has become increasingly important in many real-world applications. Limited by the computing power of sensor-side hardwa…
Hybrid Beamforming Design for Bistatic Integrated Sensing and Communication Systems
Tianhao Mao, Jie Yang, Le Liang +1
Integrated sensing and communication (ISAC) in millimeter wave is a key enabler for next-generation networks, which leverages large bandwidth and extensive antenna arrays, benefiti…
Beam Prediction based on Large Language Models
Yucheng Sheng, Kai Huang, Le Liang +3
In this letter, we use large language models (LLMs) to develop a high-performing and robust beam prediction method. We formulate the millimeter wave (mmWave) beam prediction proble…