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

--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. 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. HE air-ground network is a foundational infrastructure for networked intelligence and low-altitude economy, addressing safety and efficiency needs in intelligent transportation, autonomous logistics, and other next-generation applications [1]. These networks require high-speed data transmission and precise sensing capabilities [2]. Base stations (BS) must ensure the quality of services for communication users, such as mobile ground vehicles, while localizing low-altitude unmanned aerial vehicles (UA Vs).