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The Analog Designer’s Toolbox (ADT): Towards A New Paradigm for Analog IC Design

Virtual - Zoom

The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Dr. Hesham Omran of Ain Shams University. This event will be a virtual talk held on Zoom. The invitation will be sent to registerants. Topic: The Analog Designer's Toolbox (ADT): Towards A New Paradigm for Analog IC Design Abstract: The integrated circuit (IC) technology has witnessed an exponential advancement in the last decades and has changed every aspect in our life. On the other hand, the analog IC design flow did not experience any major change since the introduction of Berkeley SPICE in the 1970s, posing significant challenges to the design of complex systems and to the transfer of analog design expertise and knowledge. The Analog Designer’s Toolbox (ADT) is an analog EDA tool that addresses this problem by defining a new paradigm in analog IC design. ADT provides a turnkey solution that enables everyone to reap the benefits of the gm/ID design methodology powered by precomputed lookup tables (LUTs). At the device level, ADT Device Xplore gives an easy interface to plot arbitrary design charts involving complex expressions. The designer can explore devices from different technologies at different corners and temperatures, and extract simulator-accurate design points while taking second-order effects into consideration. At the block level, ADT Design Xplore gives the designer the power of design space exploration, constraints management, live tuning, and optimization, all in a single cockpit without invoking the simulator. Moreover, with a single click, ADT can build the testbenches in the background and report the results from your favorite simulator. The aim of ADT is to boost productivity, restore designer’s intuition, and make the design process systematic, optimized, and fun! Speaker: Hesham Omran Biography: Dr. Hesham Omran received the B.Sc. (with honors) and M.Sc. degrees from Ain Shams University, Cairo, Egypt, in 2007 and 2010, respectively, and the Ph.D. degree from King Abdullah University of Science and Technology (KAUST), Saudi Arabia, in 2015, all in Electrical Engineering. From 2008 to 2011, he was a Design Engineer with Si-Ware Systems (SWS), Cairo, Egypt, where he worked on the circuit and system design of the first miniaturized FT-IR MEMS spectrometer (NeoSpectra), and a Research and Teaching Assistant with the Integrated Circuits Lab (ICL), Ain Shams University. From 2011 to 2016 he was a Researcher with the Sensors Lab, KAUST. He held internships with Bosch Research and Technology Center, CA, USA, and with Mentor Graphics, Cairo, Egypt. In 2016, he rejoined the ICL, Ain Shams University, as an Assistant Professor. He developed and taught several advanced courses on different topics in the field of IC Design. Most of these courses are available on the Mastering Microelectronics YouTube channel with 4k+ subscribers. He co-founded Master Micro in 2020 to develop the Analog Designer’s Toolbox (ADT), a winner of the Egyptian ITIDA-TIEC startup incubation program. Dr. Hesham has received several awards including the Egyptian State Encouragement Award for Engineering Sciences in 2019, best paper award from the IEEE International Design and Test Conference in 2009, and Academic Excellence Awards from KAUST and Ain Shams University in 2011 and 2002, respectively. He has published 40+ papers in international journals and conferences. He serves as a reviewer for several international journals and conferences including IEEE Transactions on Circuits and Systems (TCAS) I & II, IEEE Transactions on Instrumentation and Measurement, and IEEE Transactions on Very Large Scale Integration Systems (TVLSI). His research interests are in the design of analog and mixed-signal integrated circuits, and especially in analog and mixed-signal CAD tools and design automation. Email: hesham.omran@master-micro.com

IEEE VDL: Deep Learning for Physical Layer Communications: An Attempt towards 6G

Kingston, Ontario, Canada, Virtual: https://events.vtools.ieee.org Kingston, Ontario, Canada, Virtual: https://events.vtools.ieee.org

Join us for the IEEE Virtual Distinguished Lecture "Deep Learning for Physical Layer Communications: An Attempt towards 6G" presented by Prof. Feifei Gao of Tsinghua University, China. Contact: IEEE Kingston ComSoc Chapter Abstract: Merging artificial intelligence into the system design has appeared as a new trend in wireless communications areas and has been deemed as one of the 6G technologies. In this talk, we will present how to apply the deep neural network (DNN) for various aspects of physical layer communications design, including the channel estimation, channel prediction, channel feedback, data detection, and beamforming, etc. We will also present a promising new approach that is driven by both the communications data and the communication models. It will be seen that the DNN can be used to enhance the performance of the existing technologies once there is model mismatch. More interestingly, we will show that applying DNN can deal with the conventionally unsolvable problems, thanks to the universal approximation capability of DNN. With the well-defined propagation model in communication areas, we also attempt to explain the DNN under the scenario of channel estimation and reach a strong conclusion that DNN can always provide the asymptotically optimal channel estimations. We have also build test-bed to show the effectiveness of the AI aided wireless communications. In all, DNN is shown to be a very powerful tool for communications and would make the communications protocols more intelligently. Nevertheless, as a new born stuff, one should carefully select suitable scenarios for applying DNN rather than simply spreading it everywhere. Biography: Prof. Gao's research interest include signal processing for communications, array signal processing, convex optimizations, and artificial intelligence assisted communications. He has authored/ coauthored more than 150 refereed IEEE journal papers and more than 150 IEEE conference proceeding papers that are cited more than 10000 times in Google Scholar. Prof. Gao has served as an Editor of IEEE Transactions on Wireless Communications, IEEE Journal of Selected Topics in Signal Processing (Lead Guest Editor), IEEE Transactions on Cognitive Communications and Networking, IEEE Signal Processing Letters, IEEE Communications Letters, IEEE Wireless Communications Letters, and China Communications. He has also serves as the symposium co-chair for 2019 IEEE Conference on Communications (ICC), 2018 IEEE Vehicular Technology Conference Spring (VTC), 2015 IEEE Conference on Communications (ICC), 2014 IEEE Global Communications Conference (GLOBECOM), 2014 IEEE Vehicular Technology Conference Fall (VTC), as well as Technical Committee Members for more than 50 IEEE conferences.

Reconfigurable Intelligent Surfaces: A Signal Processing Perspective

Montreal, Quebec Canada

Wireless connectivity is becoming as essential as electricity in our modern world. Although we would like to deliver wireless broadband services everywhere, the underlying physics makes it inherently complicated: the signal power vanishes very quickly with the propagation distance and is absorbed or scattered when interacting with objects in the way. Even when we have a “strong" signal, only one in a million parts of the signal energy is being received, thus, there is a huge room for improvements! What if we could tune the propagation environment to our needs? This is the main goal of reconfigurable intelligent surfaces, which is an emerging concept for beyond-5G communications. The idea is to support the transmission from a source to a destination by deploying so-called metasurfaces that can reconfigure how incident signal waves are scattered. These surfaces can be electronically configured to interact with the wireless signals as if they had different shapes. For example, it can be configured to behave as a parabolic reflector that is rotated to gather signal energy and re-radiates it as a beam focused on the receiver. This feature makes use of a new design dimension: we can not only optimize the transmitter and receiver but also control the channel. This might be a game-changer when communicating at mmWave and THz frequencies, where the traditional propagation conditions are particularly cumbersome. This might sound like science fiction but is theoretically possible. In this talk, Dr. Emil will explain the fundamentals of this new technology from a signal processing perspective. By deriving a signals-and-systems description, we can look beyond the initial hype and understand what is actually happening when using reconfigurable intelligent surfaces. Dr. Emil will also describe recent experimental validations of the fundamentals. The talk will culminate in a description of the main research challenges that need to be tackled in the coming years. The virtual platform information will be sent to registrants a couple of hours ahead of starting the event. Contact: IEEE Young Professionals Montreal Speaker: Emil Björnson Biography: Emil Björnson received the M.S. degree in engineering mathematics from Lund University, Sweden, in 2007, and the Ph.D. degree in telecommunications from the KTH Royal Institute of Technology, Sweden, in 2011. From 2012 to 2014, he held a joint post-doctoral position at the Alcatel-Lucent Chair on Flexible Radio, SUPELEC, France, and the KTH Royal Institute of Technology. He joined Linköping University, Sweden, in 2014, where he is currently an Associate Professor. In September 2020, he became a part-time Visiting Full Professor at the KTH Royal Institute of Technology. He has authored the textbooks Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013), Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency (2017), and Foundations of User-Centric Cell-Free Massive MIMO (2021). He is dedicated to reproducible research and has made a large amount of simulation code publicly available. He performs research on MIMO communications, radio resource allocation, machine learning for communications, and energy efficiency. He has been on the Editorial Board of the IEEE Transactions on Communications since 2017. He has been a member of the Online Editorial Team of the IEEE Transactions on Wireless Communications since 2020. He has been an Area Editor in IEEE Signal Processing Magazine since 2021. He has performed MIMO research for over 14 years, his papers have received more than 12000 citations, and he has filed more than twenty patent applications. He is a host of the podcast Wireless Future and has a popular YouTube channel. He has received the 2014 Outstanding Young Researcher Award from IEEE ComSoc EMEA, the 2015 Ingvar Carlsson Award, the 2016 Best Ph.D. Award from EURASIP, the 2018 IEEE Marconi Prize Paper Award in Wireless Communications, the 2019 EURASIP Early Career Award, the 2019 IEEE Communications Society Fred W. Ellersick Prize, the 2019 IEEE Signal Processing Magazine Best Column Award, the 2020 Pierre-Simon Laplace Early Career Technical Achievement Award, and the 2020 CTTC Early Achievement Award. He also co-authored papers that received Best Paper Awards at the conferences, including WCSP 2009, the IEEE CAMSAP 2011, the IEEE SAM 2014, the IEEE WCNC 2014, the IEEE ICC 2015, and WCSP 2017.