# Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network

arXiv: https://arxiv.org/abs/2506.12831 · HTML: https://mlsanity.com/paper/2506.12831/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 30 of its 49 references that are in the map.
- First posted on arXiv 15 Jun 2025.

## Builds on (most cited first, 30 of 30)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [Vision-Aided 6G Wireless Communications: Blockage Prediction and Proactive Handoff](https://mlsanity.com/paper/2102.09527/) (2021)
- [A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence](https://mlsanity.com/paper/2010.09317/) (2020)
- [Intelligent Multi-Modal Sensing-Communication Integration: Synesthesia of Machines](https://mlsanity.com/paper/2306.14143/) (2023)
- [An Overview of 5G Advanced Evolution in 3GPP Release 18](https://mlsanity.com/paper/2201.01358/) (2022)
- [Cram'er-Rao Bound Optimization for Joint Radar-Communication Design](https://mlsanity.com/paper/2101.12530/) (2021)
- [Single Image Dehazing Using Ranking Convolutional Neural Network](https://mlsanity.com/paper/2001.05246/) (2020)
- [Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey](https://mlsanity.com/paper/2301.03857/) (2023)
- [Bayesian Predictive Beamforming for Vehicular Networks: A Low-overhead Joint Radar-Communication Approach](https://mlsanity.com/paper/2005.07698/) (2020)
- [Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning](https://mlsanity.com/paper/2207.03046/) (2022)
- [Integrated Sensing and Communications Towards Proactive Beamforming in mmWave V2I via Multi-Modal Feature Fusion (MMFF)](https://mlsanity.com/paper/2310.02561/) (2023)
- [SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM)](https://mlsanity.com/paper/2501.07459/) (2025)
- [Integrated Sensing and Communication with mmWave Massive MIMO: A Compressed Sampling Perspective](https://mlsanity.com/paper/2201.05766/) (2022)
- [Estimating Doubly-Selective Channels for Hybrid mmWave Massive MIMO Systems: A Doubly-Sparse Approach](https://mlsanity.com/paper/1912.08380/) (2019)
- [Deep Learning Based Channel Covariance Matrix Estimation with User Location and Scene Images](https://mlsanity.com/paper/2101.07471/) (2021)
- [THz ISAC: A Physical-Layer Perspective of Terahertz Integrated Sensing and Communication](https://mlsanity.com/paper/2209.03145/) (2022)
- [Unsupervised Learning for Joint Beamforming Design in RIS-aided ISAC Systems](https://mlsanity.com/paper/2403.17324/) (2024)
- [A Unified 3D Beam Training and Tracking Procedure for Terahertz Communication](https://mlsanity.com/paper/2110.01066/) (2021)
- [On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective](https://mlsanity.com/paper/2211.00434/) (2022)
- [YOLO: An Efficient Terahertz Band Integrated Sensing and Communications Scheme with Beam Squint](https://mlsanity.com/paper/2305.12064/) (2023)
- [A LiDAR-Aided Channel Model for Vehicular Intelligent Sensing-Communication Integration](https://mlsanity.com/paper/2403.14185/) (2024)
- [Synesthesia of Machines (SoM)-Enhanced ISAC Precoding for Vehicular Networks with Double Dynamics](https://mlsanity.com/paper/2408.13546/) (2024)
- [Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks](https://mlsanity.com/paper/2103.01829/) (2021)
- [Spatial-chirp Codebook-based Hierarchical Beam Training for Extremely Large-Scale Massive MIMO](https://mlsanity.com/paper/2210.03345/) (2022)
- [RIS-assisted Integrated Sensing and Communications: A Subspace Rotation Approach](https://mlsanity.com/paper/2210.13987/) (2022)
- [Joint Delay-Phase Precoding Under True-Time Delay Constraints in Wideband Sub-THz Hybrid Massive MIMO Systems](https://mlsanity.com/paper/2212.07484/) (2022)
- [Hybrid Arrays: How Many RF Chains Are Required to Prevent Beam Squint?](https://mlsanity.com/paper/2310.07101/) (2023)
- [Superposed IM-OFDM (S-IM-OFDM): An Enhanced OFDM for Integrated Sensing and Communications](https://mlsanity.com/paper/2403.13314/) (2024)
- [Synesthesia of Machine (SoM)-Driven Analog Precoder Optimization for Enhanced ISAC Performance in Sub-THz Systems](https://mlsanity.com/paper/2412.13532/) (2024)

## Abstract (arXiv)

Integrated sensing and communication (ISAC) within sub-THz frequencies is crucial for future air-ground networks, but unique propagation characteristics and hardware limitations present challenges in optimizing ISAC performance while increasing operational latency. This paper introduces a multi-modal sensing fusion framework inspired by synesthesia of machine (SoM) to enhance sub-THz ISAC transmission. By exploiting inherent degrees of freedom in sub-THz hardware and channels, the framework optimizes the radio-frequency environment. Squint-aware beam management is developed to improve air-ground network adaptability, enabling three-dimensional dynamic ISAC links. Leveraging multi-modal information, the framework enhances ISAC performance and reduces latency. Visual data rapidly localizes users and targets, while a customized multi-modal learning algorithm optimizes the hybrid precoder. A new metric provides comprehensive performance evaluation, and extensive experiments demonstrate that the proposed scheme significantly improves ISAC efficiency.