Wed, 11 May, 12:00 - 12:45 UTC
Future communication networks must address the scarce spectrum to accommodate the extensive growth of heterogeneous wireless devices. Efforts are underway to address spectrum coexistence, enhance spectrum awareness, and bolster authentication schemes. Wireless signal recognition is becoming increasingly more significant for spectrum monitoring, spectrum management, secure communications, among others. Along with spectrum crunch and throughput challenges, such a massive scale of wireless devices exposes unprecedented threat surfaces. RF fingerprinting is heralded as a candidate technology that can be combined with cryptographic and zero-trust security measures to ensure data privacy, confidentiality, and integrity in wireless networks. Consequently, comprehensive spectrum awareness on the edge has the potential to serve as a key enabler for the emerging beyond 5G networks.
Signal Intelligence (SIGINT) can be referred to as a technique with the objective of characterizing unknown RF signals providing actionable information to the remaining components of the communication systems. State-of-the-art studies in this domain have (i) only focused on a single task - modulation or signal (protocol) or emitter classification - which in many cases is insufficient information for a system to act on, and (ii) does not address edge deployment during the neural network design phase. Motivated by the relevance of this subject in the context of advanced signal processing for future communication networks, in this talk, I will discuss some of the recent work performed to overcome the challenges and the related findings. Next, we describe some of the active areas of research in the domain to motivate several of the open problems and opportunities. Thereafter, we pave a path forward providing research direction to enhance these capabilities over the next few years. ICAASP being the flagship conference for IEEE Signal Processing Society, would be the perfect venue to present these ideas and motivation for researchers to solve and contribute towards this exciting field of research and development.
Biography
Dr. Jithin Jagannath is the Chief Technology Scientist and Founding Director of the Marconi-Rosenblatt AI/ML Innovation Lab at ANDRO Computational Solutions. He is also the Adjunct Assistant Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. Dr. Jagannath received his Ph.D. degree in Electrical Engineering from Northeastern University. He is an IEEE Senior member and serves as an IEEE Industry DSP Technology Standing Committee member. He also serves on the Federal Communication Commission's (FCC) Communications Security, Reliability, and Interoperability Council (CSRIC VIII) Working Group 1. Dr. Jagannath was the recipient of the 2021 IEEE Region 1 Technological Innovation Award with the citation, "For innovative contributions in machine learning techniques for the wireless domain''.
Dr. Jagannath heads several of the ANDRO's research and development projects in the field of Beyond 5G, signal processing, RF signal intelligence, cognitive radio, cross-layer ad-hoc networks, Internet-of-Things, AI-enabled wireless, and machine learning. He has been the Technical Lead and Principal Investigator (PI) of several multi-million dollar research projects at ANDRO. This includes a Rapid Innovation Fund (RIF) and several Small Business Innovation Research (SBIR)s for several customers including the U.S. Army, U.S Navy, USSOCOM, and Department of Homeland Security (DHS). He is the inventor of 11 U.S. Patents (granted, pending, and provisional). He has been invited to give various talks including Keynote on the topic of machine learning and Beyond 5G wireless communication. He has been invited to serve on the Technical Program Committee for several leading technical conferences.