From Intelligent Surfaces to Noise-Driven Communication: Innovative Technologies for 6G and Beyond

Table of Contents

Seminars-2-2024 - This article is part of a series.

Part 1: The Dawn of an Immersive Internet: XR, Generative AI and the Road to 6G

Part 2: AGI Chips - The Next Frontier

Part 3: Generalist vs Specialist Language Models

Part 4: This Article

Part 5: An Overview of Evolutionary Multi-Objective Optimization

Part 6: Packet Trimming at the Edge for Low Latency in 6G Environments

Part 7: Scientific Machine Learning and Quantum Utility: A Near Future Perspective

Part 8: Cloud Storage Systems: Latency Characterization and Extensions

Part 9: Let the Plants do the Talking: Climate-Smart Agriculture by the Messages Received from Plants and Soil

Part 10: More is different: How the Science of Complex Systems can inspire Future Autonomous Networks

Abstract #

Our community has witnessed the rise of many exciting communication technologies in recent years. Notable examples include alternative waveforms, massive multiple-input multiple-output signaling, non-orthogonal multiple access, joint communications and sensing, AI-empowered systems, and so on. In this context, 6G wireless networks will inevitably require a rethinking of wireless communication systems and technologies, particularly at the physical layer, since the cellular industry reached another critical milestone with the development of 5G wireless networks with diverse applications. Within this perspective, first, this talk aims to shed light on the most recent developments in reconfigurable intelligent surface (RIS)-empowered communication towards 6G and beyond wireless networks by discussing promising candidates for future research and development. Specifically, we emphasize different RIS architectures and emerging RIS use cases. Second, taking RIS-based radio frequency chain-free transmitters one step further, we put forward the paradigm of noise-driven communication. We discuss the potential of noise-driven communication systems for three purposes: low/zero-signal-power transmission by indexing resistors or other noise sources according to information bits, noise-alike waveform/modulation design for improved communication efficiency, and unconditionally secure key generation using noise-based loops.

Bio of Ertuğrul Başar #

Prof. Ertuğrul Başar received his Ph.D. degree from Istanbul Technical University in 2013. He is a Professor at the Department of Electrical and Electronics Engineering, Koç University, Istanbul, Turkey, and the director of the Communications Research and Innovation Laboratory (CoreLab). He had visiting positions at Ruhr University Bochum, Germany (2022, Mercator Fellow) and Princeton University, USA (2011-2012, Visiting Research Collaborator). His primary research interests include 6G and beyond wireless networks, communication theory and systems, reconfigurable intelligent surfaces, software-defined radio implementations, waveform design, physical layer security, and deep learning and signal processing for communications. In the past, Dr. Başar served as an Editor/Senior Editor for many journals, including IEEE Communications Letters (2016-2022), IEEE Transactions on Communications (2018-2022), Physical Communication (2017-2020), and IEEE Access (2016-2018). Currently, he is an Editor of Frontiers in Communications and Networks. He is the author/co-author of more than 170 international journal publications and 16 patents that received around 15K citations. He also supervised 5 PhD and 18 master’s students. He is an Associate Member of the Turkish Academy of Sciences (TÜBA). In recognition of his outstanding contributions to physical-layer design for next-generation wireless networks, Prof. Basar was elevated to IEEE Fellow in 2023, becoming one of the youngest IEEE Fellows of Turkey at the age of 37. He is also a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) and the Artificial Intelligence Industry Academy (AIIA). Recently, Dr. Basar has been selected as an IEEE ComSoc Distinguished Lecturer for the Class of 2024-2025.