11 papers · 1 filter
WiCo-PG: Wireless Channel Foundation Model for Pathloss Map Generation via Synesthesia of Machines
Mingran Sun, Lu Bai, Ziwei Huang +3
A wireless channel foundation model for pathloss map generation (WiCo-PG) via Synesthesia of Machines (SoM) is developed for the first time. Considering sixth-generation (6G) uncre…
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…
SynthSoM-Twin: A Multi-Modal Sensing-Communication Digital-Twin Dataset for Sim2Real Transfer via Synesthesia of Machines
Junlong Chen, Ziwei Huang, Xuesong Cai +2
This paper constructs a novel multi-modal sensing-communication digital-twin dataset, named SynthSoM-Twin, which is spatio-temporally consistent with the real world, for Sim2Real t…
LLM4PG: Adapting Large Language Model for Pathloss Map Generation via Synesthesia of Machines
Mingran Sun, Lu Bai, Xiang Cheng +1
In this paper, a novel large language model (LLM)-based pathloss map generation model, termed LLM4PG, is proposed for sixth-generation (6G) AI-native communication systems via Syne…
LLM4MG: Adapting Large Language Model for Multipath Generation via Synesthesia of Machines
Ziwei Huang, Shiliang Lu, Lu Bai +2
Based on Synesthesia of Machines (SoM), a large language model (LLM) is adapted for multipath generation (LLM4MG) for the first time. Considering a typical sixth-generation (6G) ve…
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…
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…
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…
A Multi-modal Intelligent Channel Model for 6G Multi-UAV-to-Multi-Vehicle Communications
Lu Bai, Mengyuan Lu, Ziwei Huang +1
In this paper, a novel multi-modal intelligent channel model for sixth-generation (6G) multiple-unmanned aerial vehicle (multi-UAV)-to-multi-vehicle communications is proposed. To…
Synesthesia of Machines Based Multi-Modal Intelligent V2V Channel Model
Zengrui Han, Lu Bai, Ziwei Huang +1
This paper proposes a novel sixth-generation (6G) multi-modal intelligent vehicle-to-vehicle (V2V) channel model from light detection and ranging (LiDAR) point clouds based on Syne…
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…