9 papers
WiFo-INR: A Wireless Foundation Model Based on Implicit Neural Representations
Boxun Liu, Xuanyu Liu, Shijian Gao +2
Wireless foundation models are emerging as a promising paradigm for AI-native physical-layer design. However, existing methods typically model channel state information (CSI) as im…
WiFo-MiSAC: A Wireless Foundation Model for Multimodal Sensing and Communication Integration via Synesthesia of Machines (SoM)
Xuanyu Liu, Shijian Gao, Boxun Liu +2
Current learning-based wireless methods struggle with generalization due to the fragmented processing of communication and sensing data. WiFo-MiSAC addresses this as a task-agnosti…
Large Wireless Foundation Models: Stronger over Bigger
Xiang Cheng, Boxun Liu, Xuanyu Liu +1
AI-communication integration is widely regarded as a core enabling technology for 6G. Most existing AI-based physical-layer designs rely on task-specific models that are separately…
WiFo-2: a generalist foundation model unifies heterogeneous wireless system design
Boxun Liu, Xuanyu Liu, Shijian Gao +3
Emerging sixth-generation wireless systems are increasingly heterogeneous, with compatibility across diverse configurations, ubiquitous coverage, and expanded functionalities. Alth…
WiFo-CF: Wireless Foundation Model for CSI Feedback
Xuanyu Liu, Shijian Gao, Boxun Liu +2
Deep learning-based channel state information (CSI) feedback schemes demonstrate strong compression capabilities but are typically constrained to fixed system configurations, limit…
Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration
Xiang Cheng, Boxun Liu, Xuanyu Liu +2
To support future intelligent multifunctional sixth-generation (6G) wireless communication networks, Synesthesia of Machines (SoM) is proposed as a novel paradigm for artificial in…
LLM4WM: Adapting LLM for Wireless Multi-Tasking
Xuanyu Liu, Shijian Gao, Boxun Liu +2
The wireless channel is fundamental to communication, encompassing numerous tasks collectively referred to as channel-associated tasks. These tasks can leverage joint learning base…
WiFo: Wireless Foundation Model for Channel Prediction
Boxun Liu, Shijian Gao, Xuanyu Liu +2
Channel prediction permits to acquire channel state information (CSI) without signaling overhead. However, almost all existing channel prediction methods necessitate the deployment…
LLM4CP: Adapting Large Language Models for Channel Prediction
Boxun Liu, Xuanyu Liu, Shijian Gao +2
Channel prediction is an effective approach for reducing the feedback or estimation overhead in massive multi-input multi-output (m-MIMO) systems. However, existing channel predict…