32 papers
Foundation Models for Wireless Communications: From PHY Intelligence to Network Autonomy
Le Liang, Jiajia Guo, Jun Zhang +6
6G networks will introduce unprecedented complexity, which calls for a paradigm shift in network optimization and management. Artificial intelligence (AI)-based solutions, especial…
A Graph Foundation Model for Wireless Resource Allocation
Yucheng Sheng, Jiacheng Wang, Le Liang +2
The aggressive densification of modern wireless networks necessitates judicious resource allocation to mitigate severe mutual interference. However, classical iterative algorithms…
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…
Beam Prediction Based on Multimodal Large Language Models
Tianhao Mao, Le Liang, Jie Yang +3
Accurate beam prediction is a key enabler for next-generation wireless communication systems. In this paper, we propose a multimodal large language model (LLM)-based beam predictio…
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.…
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…