3 citations · 3 across the 21 of their papers we have counts for
8 papers · 1 filter
Embodied Intelligent Wireless (EIW): Synesthesia of Machines Empowered Wireless Communications
Xiang Cheng, Weibo Wen, Haotian Zhang +4
The evolution toward the sixth-generation (6G) and beyond mobile communication systems is marked by a fundamental shift from merely connecting devices to enabling pervasive and emb…
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…
Tiny-WiFo: A Lightweight Wireless Foundation Model for Channel Prediction via Multi-Component Adaptive Knowledge Distillation
Haotian Zhang, Shijian Gao, Xiang Cheng
The massive scale of Wireless Foundation Models (FMs) hinders their real-time deployment on edge devices. This letter moves beyond standard knowledge distillation by introducing a…
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…
Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network
Zonghui Yang, Shijian Gao, Xiang Cheng +1
Integrated sensing and communication (ISAC) within sub-THz frequencies is crucial for future air-ground networks, but unique propagation characteristics and hardware limitations pr…
Synesthesia of Machines (SoM)-Aided Online FDD Precoding via Heterogeneous Multi-Modal Sensing: A Vertical Federated Learning Approach
Haotian Zhang, Shijian Gao, Weibo Wen +2
This paper investigates a heterogeneous multi-vehicle, multi-modal sensing (H-MVMM) aided online precoding problem. The proposed H-MVMM scheme utilizes a vertical federated learnin…
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…
Synesthesia of Machines (SoM)-Aided FDD Precoding with Sensing Heterogeneity: A Vertical Federated Learning Approach
Haotian Zhang, Shijian Gao, Weibo Wen +1
High complexity in precoding design for frequency division duplex systems necessitates streamlined solutions. Guided by Synesthesia of Machines (SoM), this paper introduces a heter…