7 papers
A Multi-Modal Intelligent U2V Channel Model for 6G Sensing-Communication Integration
Shuo Wang, Zengrui Han, Lu Bai +1
This paper proposes a novel UAV-to-Vehicle (U2V) channel model for sixth-generation (6G) intelligent sensing-communication integration, based on three-dimensional (3D) scatterer pr…
Multi-Modal Intelligent Channel Modeling: From Fine-tuned LLMs to Pre-trained Foundation Models
Lu Bai, Zengrui Han, Mingran Sun +1
To meet the evolving demands of sixth-generation (6G) wireless channel modeling, such as precise prediction capability, extension capabilities, and system participation capability,…
WiCo-MG: Wireless Channel Foundation Model for Multipath Generation via Synesthesia of Machines
Zengrui Han, Lu Bai, Xuesong Cai +1
Precise modeling of channel multipath is essential for understanding wireless propagation environments and optimizing communication systems. In particular, sixth-generation (6G) ar…
Multi-Modal Intelligent Channel Modeling Framework for 6G-Enabled Networked Intelligent Systems
Lu Bai, Zengrui Han, Xuesong Cai +1
The design and technology development of 6G-enabled networked intelligent systems needs an accurate real-time channel model as the cornerstone. However, with the new requirements o…
LLM4SG: Adapting Large Language Model for Scatterer Generation via Synesthesia of Machines
Zengrui Han, Lu Bai, Ziwei Huang +1
In this paper, a novel large language model (LLM)-based method for scatterer generation (LLM4SG) is proposed for sixth-generation (6G) artificial intelligence (AI)-native communica…
SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM)
Xiang Cheng, Ziwei Huang, Yong Yu +5
Given the importance of datasets for sensing-communication integration research, a novel simulation platform for constructing communication and multi-modal sensory dataset is devel…