The communication, sensing, and wireless-IoT is undergoing massive scaling. This increases the demand for intelligent spectrum access facilitated through the perception of the electromagnetic environment. Sensing and perception of the RF spectrum is crucial for the coexistence of a multitude of systems. The radio spectrum can be sensed and perceived using AI/ML approaches. Linear algebra is the workhorse mathematical framework for all types of sensing (i.e., beamforming), modulation and multiplexing (e.g., OFDM), and AI/ML algorithms.
The proposed workshop titled Linear Algebra and Signal Processing in AI/ML for Spectrum Awareness aims to cover recent advancements in linear algebra, signal processing, and their applications while addressing spectrum challenges such as interference, congestion, and noise. We explore linear algebra and signal processing to furnish modern wireless communications, sensing, and spectral perception systems. Given the pervasive role of spectrum awareness in relevant industries, including telecommunications, defense, passive sensing, radio science, and IoT/industry 4.0, we anticipate a broad interest among professionals, academicians, and students. Such diversity in the target audience will lead to a significant turnout. To attract a wide range of attendees who are eager to learn from leaders in both theoretical and practical applications, we hope that the workshop theme is designed to feature prominent speakers and experts in the field.
