collaborators

13 papers

cs.IT2026

Wireless Power Control Based on Large Language Models

Jiacheng Wang, Yucheng Sheng, Le Liang +2

This paper investigates the power control problem in wireless networks by repurposing pre-trained large language models (LLMs) as relational reasoning backbones. In hyper-connected…

cs.AI2026

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.…

cs.IT2026

Reducing Pilots in Channel Estimation with Predictive Foundation Models

Xingyu Zhou, Le Liang, Hao Ye +3

Accurate channel state information (CSI) acquisition is essential for modern wireless systems, which becomes increasingly difficult under large antenna arrays, strict pilot overhea…

eess.SP2026

Multimodal-Wireless: A Large-Scale Dataset for Sensing and Communication

Tianhao Mao, Le Liang, Jie Yang +3

This paper presents Multimodal-Wireless, a large-scale open-source dataset for multimodal sensing and communication research. The dataset is generated through an integrated and cus…

eess.SP2025

Cross-Modal Semantic Communication for Heterogeneous Collaborative Perception

Mingyi Lu, Guowei Liu, Le Liang +3

Collaborative perception, an emerging paradigm in autonomous driving, has been introduced to mitigate the limitations of single-vehicle systems, such as limited sensor range and oc…

eess.SY2025

RSU-Assisted Resource Allocation for Collaborative Perception

Guowei Liu, Le Liang, Chongtao Guo +2

As a pivotal technology for autonomous driving, collaborative perception enables vehicular agents to exchange perceptual data through vehicle-to-everything (V2X) communications, th…