# SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM)

arXiv: https://arxiv.org/abs/2501.07459 · HTML: https://mlsanity.com/paper/2501.07459/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2025.

## Built on by (most cited first, 7 of 7)

- [Great X: A Unified Multi-Modal Simulator Bridging the Sim2Real Gap for 6G](https://mlsanity.com/paper/2507.08716/) (2025)
- [Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks](https://mlsanity.com/paper/2512.01750/) (2025)
- [Large Model Enabled Embodied Intelligence for 6G Integrated Perception, Communication, and Computation Network](https://mlsanity.com/paper/2512.15109/) (2025)
- [Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network](https://mlsanity.com/paper/2506.12831/) (2025)
- [Synesthesia of Vehicles: Tactile Data Synthesis from Visual Inputs](https://mlsanity.com/paper/2602.01832/) (2026)
- [Wireless Foundation Models: State-of-the-Art and Open Challenges](https://mlsanity.com/paper/2609.04707/) (2026)
- [Link Both Views: Cross-Image Routing Attention for Dual-Endpoint V2I Beam-Pair Power Prediction](https://mlsanity.com/paper/2610.18195/) (2026)

## Abstract (arXiv)

Given the importance of datasets for sensing-communication integration research, a novel simulation platform for constructing communication and multi-modal sensory dataset is developed. The developed platform integrates three high-precision software, i.e., AirSim, WaveFarer, and Wireless InSite, and further achieves in-depth integration and precise alignment of them. Based on the developed platform, a new synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM), named SynthSoM, is proposed. The SynthSoM dataset contains various air-ground multi-link cooperative scenarios with comprehensive conditions, including multiple weather conditions, times of the day, intelligent agent densities, frequency bands, and antenna types. The SynthSoM dataset encompasses multiple data modalities, including radio-frequency (RF) channel large-scale and small-scale fading data, RF millimeter wave (mmWave) radar sensory data, and non-RF sensory data, e.g., RGB images, depth maps, and light detection and ranging (LiDAR) point clouds. The quality of SynthSoM dataset is validated via statistics-based qualitative inspection and evaluation metrics through machine learning (ML) via real-world measurements. The SynthSoM dataset is open-sourced and provides consistent data for cross-comparing SoM-related algorithms.