Title: Intelligent Reflecting Surfaces: Fundamentals, Challenges, Applications and Deep Learning-Based Solutions

Bio: Sanjeev Gurugopinath obtained his PhD in signal processing for communications from the Indian Institute of Science, Bangalore. He is currently the engineering director (AI/software) at MMRFIC technology private limited, Bengaluru and a professor in the department of Electronics and Communication Engineering at PES University, Bengaluru. His research interests are in the areas of signal processing for millimeter-wave communications, next-generation communication systems, power line communications, underwater acoustics and speech signal processing. He is a co-recipient of the best paper awards at several IEEE conferences.

Abstract: In this talk, we first introduce the concept of intelligent reflecting surfaces (IRS) by motivating it from the perspective of next-generation wireless communication systems. Next, we present a detailed study on the mathematical models for IRS-based communications, and discuss key applications. Later, we review various academic and industrial test benches and prototypes developed with an emphasis on the challenges involved and possible deep learning (DL)-based solutions. Furthermore, we discuss the future research trends and the potential of IRS to coexist with other 6G-related technologies. Finally, we discuss a specific problem of beamforming design and data detection in IRS and present a deep learning-based solution.

Title: Towards an AI-native communications system design

Bio: Kapil Bhattad received his B. Tech degree in Electrical Engineering from IIT Madras in 2002 and a Ph.D. degree in Electrical Engineering from Texas A&M University in 2007. He has been at Qualcomm research since then in San Diego from 2007 to 2011 and in Bangalore from 2011 onwards. He has contributed extensively to design, standardization, and commercialization of wireless communication technologies and chipsets covering 3G,4G,5G, IoT, and satellite communication systems. He has more than 250 patent applications in these areas. He currently leads the ML for wireless and the RFPI systems team in India.

Abstract: Artificial intelligence (AI) has become an ever-present topic in recent news, captivating headlines with its remarkable advancements and transformative impact across industries. From breakthroughs in healthcare and finance to progresses in natural language processing and debates about its societal implications, AI’s influence is growing rapidly, and it is poised to fundamentally reshape our future. In the world of wireless communications, AI is changing how we approach and solve difficult technical challenges, and it is expected to play an instrumental role in every part of the end-to-end cellular system design.

In this talk we will explore the profound impact of AI on wireless communications:

• Take a closer look at how AI can substantively improve wireless system performance.


• See wireless AI in action by taking a deeper dive into our latest technology demonstrations.


• Understand what wireless AI capabilities 5G Advanced Release 18/19 will bring


• Discover key areas of our wireless AI research and how 6G will become the first AI-native cellular generation

Title: Fundamentals of Reconfigurable Intelligent Surfaces and its Benefits in Communication and Sensing

Bio: Praful D. Mankar (Member, IEEE) received the bachelor’s degree in electrical and communication engineering from Amravati University, India, in 2006, and the master’s degree in telecommunications systems engineering and the Ph.D. degree in wireless networks from the Indian Institute of Technology Kharagpur, India, in 2009 and 2016, respectively. He also worked as a Postdoctoral Research Associate with Wireless@Virginia Tech Research Group with Virginia Tech, Blacksburg, VA, USA, from 2017 to 2019. Since 2020, he has been working as an Assistant Professor of the Signal Processing and Communication Research Center with the International Institute of Information Technology Hyderabad, India. His research interests are wireless networks, stochastic geometry, reflecting intelligent surfaces, and the age of information.

Abstract: Throughout the last few decades, antenna array technology has played an important role in the evolution of wireless networks, spanning from the inception of 3G to the latest 5G networks. This technology enables the directional transmission and reception of wireless signals, supporting various applications such as communication, sensing, and localization. It leverages spatial multiplexing and diversity to enhance communication performance and aids in parameter estimation for sensing and localization tasks. However, its performance is often influenced by the unpredictable wireless propagation environment. Recent advancements in antenna engineering have opened up exciting possibilities, allowing us to design sub-wavelength-sized meta-materials. These materials can modify their physical properties to control the way they interact with electromagnetic signals. Integrating such elements into a planar array gives rise to a novel technology that is referred to as a 'Reconfigurable Intelligent Surface' (RIS). RIS technology offers a degree of control over wireless propagation, making it a valuable tool for shaping smart radio environments. This presentation will delve into the fundamental principles of RIS operation and explore its applications in communication and sensing.

Title: On the Optimal Deployment of Reconfigurable Intelligent Surfaces in mmWave Networks

Bio: Dr. Abhishek K. Gupta received his B.Tech.- M.Tech dual degree in Electrical Engineering from IIT Kanpur in 2010 and PhD degree in the Department of Electrical and Computer Engineering at the University of Texas at Austin in 2016. He is currently working as an assistant professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur. He heads the modern wireless networks group at IITK. His research is in the area of stochastic geometry and modern communication systems, including 5G, mmWave, THz, vehicular, and molecular communication.
He was recipient of IEI young engineer award (electronics and telecommunication discipline) by Institute of Engineers (India) in 2021, Class of 1986 young faculty fellowship by IIT Kanpur in 2022, IEEE wireless communication letters exemplary reviewer award in 2016, GE-FS leadership award by General Electric Foundation and Institute of International Education in 2009 and IITK academic excellence award for four consecutive years (2006-2009). He is author of the books, An introduction to stochastic geometry (Springer Morgan-Claypool, 2022), Numerical methods using MATLAB (Springer Apress, 2014), and MATLAB by examples (Finch, 2010). Before joining IITK, he was working as Sr. standards engineer at Samsung Research America in Dallas, TX, USA. In the past, he has worked in Applied Microelectronics Circuit Corporation (Pune), Futurewei Technologies (NJ) and Nokia Networks (IL).

Abstract: Wireless communications aided by reconfigurable intelligent surfaces (RISs) is a promising way to improve the coverage for cellular users. The controlled reflection of signals from RISs is especially useful in mm-wave/THz networks when the direct link between a cellular user and its serving base station (BS) is weak or unavailable due to blockages. However, the joint blockage of the user-RIS and the user-BS links may significantly degrade the performance of RIS-aided transmissions. In this talk, I will discuss the impact of joint blockages on RIS performance and its role in determining the optimal placements of RISs. The talk will introduce a few concepts of stochastic geometry which is a tractable tool to analyze wireless networks. I will discuss how to model mmWave networks with RISs when RIS locations are coupled with BS locations. I will discuss the optimal placement of RISs to minimize the joint blockage probability of the user-RIS and the user-BS links and maximize the downlink coverage probability. The results show that installing RISs near the cell edge of BSs usually provides optimal coverage. Moreover, deploying RISs on street intersections improves the coverage probability. For users associated with BSs that are deployed sufficiently close to intersections, the intersection-mounted RISs offer a better coverage performance as compared to BS-coupled RISs.

Title: New waveforms for Communication and Radar Sensing in 6G and Beyond

Bio: A. Chockalingam received the B.E. (Honors) degree in ECE from P. S. G. College of Technology, Coimbatore in 1984 and the M. Tech degree in E & ECE from IIT, Kharagpur in 1985. From 1986 to 1993, he was with the Satcom Lab, Transmission R & D Division, Indian Telephone Industries, Bangalore. In 1993, he obtained the Ph.D. degree in ECE from IISc, Bangalore. From 1993 to 1996, he was a postdoctoral fellow and an assistant project scientist in the Department of ECE, University of California San Diego. From 1996 to 1998, he was with Qualcomm, San Diego, as a Staff Engineer/Manager. Since 1998, he has been a faculty in the Department of ECE, IISc, where he is a professor working in the area of wireless communications.

Abstract: 6G presents an opportunity to reflect on the fundamentals of wireless communication, as it becomes more and more difficult to estimate channels in high-mobility/high-Doppler environments when information signaling and signal processing are carried out in the traditional time-frequency (TF) domain. Also, the convergence of communication and radar sensing in 6G and beyond (inspired by the developments in intelligent transportation systems) has focused research attention on the design of waveforms that support both communication as well as sensing. This talk will focus on such new waveforms for 6G and beyond, with an emphasis on orthogonal time frequency space (OTFS) waveform, which is emerging as a promising waveform for this purpose.

Information signaling and signal processing in OTFS are carried out in the delay-Doppler (DD) domain because of which OTFS outperforms traditional TF domain based multicarrier waveforms popularly used in the previous generations. A basic function in OTFS signaling is DD domain-to-time domain transformation at the transmitter and vice versa at the receiver. Last five years of OTFS research has focused on an approach where the above transformation is carried out in two steps, viz., DD domain-to-TF domain conversion using inverse symplectic finite Fourier transform (ISFFT) followed by TF domain-to-time domain conversion using Heisenberg transform, and corresponding inverse transforms at the receiver. We call this scheme OTFS 1.0. Alternately, this transformation can be carried out in a single step, viz., DD domain-to-time domain conversion using inverse Zak transform at the transmitter and time domain-to-DD domain conversion using Zak transform at the receiver. We call this scheme OTFS 2.0 (a.k.a. Zak-OTFS).

This talk will dwell on what and why of OTFS 2.0. Briefly put, OTFS 2.0 a) provides a formal mathematical framework (Zak theory) that explains why OTFS works well, b) is more robust to large channel spreads compared to OTFS 1.0, and c) has a lower complexity compared to OTFS 1.0. Research in OTFS 2.0 is wide open and we expect the next five years of OTFS research to be centered around OTFS 2.0, leading to its possible adoption in 6G standard