8 papers
Ten Years of Deep Learning for Wireless Communications: From Learned Blocks to Deployable Wireless Intelligence
Hao Ye, Geoffrey Ye Li, Biing-Hwang Juang
Over the past decade, deep learning has evolved from a tool for replacing isolated wireless blocks into a broader methodology for developing wireless intelligence. This article tra…
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…
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.…
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…
AI/ML Life Cycle Management for Interoperable AI Native RAN
Chu-Hsiang Huang, Chao-Kai Wen, Geoffrey Ye Li
Artificial intelligence (AI) and machine learning (ML) models are rapidly permeating the 5G Radio Access Network (RAN), powering beam management, channel state information (CSI) fe…