Editorial Introduction to the Special Issue on Learning-Based Signal Processing for Integrated Sensing and Communications

Signal processing techniques have played a pivotal role in the early development of joint sensing and communication systems [1]. These efforts were driven by the need to address spectrum scarcity and to reduce hardware size and cost. Initially focused on dual-function radar-communication systems, this field has since evolved into the broader paradigm of Integrated Sensing and Communication (ISAC). ISAC encompasses a wide range of interactions between sensing and communication, incorporating not just radar but also other sensors, and leveraging their capabilities for applications such as autonomous driving, drone-based services, radio-frequency identification, and weather monitoring. With wireless networks now operating at higher frequencies, their dual role as communication networks and environmental sensors has become increasingly significant, providing critical information for both user needs and network operations [2].