activity
20232026
most citedMSC: A Generic Dataset for Mixed Multi-Modal (MMM) Sensing and Communication Integration

1 citations · 2 across the 18 of their papers we have counts for

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10 papers · 1 filter

eess.SP2025

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…

eess.SP2025

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…

eess.SP2025

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…

cs.CV2025

GeoLink: Empowering Remote Sensing Foundation Model with OpenStreetMap Data

Lubian Bai, Xiuyuan Zhang, Siqi Zhang +4

Integrating ground-level geospatial data with rich geographic context, like OpenStreetMap (OSM), into remote sensing (RS) foundation models (FMs) is essential for advancing geospat…

eess.SP2025

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…

eess.SP2025

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…

eess.SP2025

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…

eess.SP2025

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…

eess.SP2025

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…

eess.SP2025

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…