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IEEE ComSoc Virtual Distinguished Lecture
This event is co-organized by the IEEE Windsor, Vancouver Joint Communications, Atlanta Central Texas, North Macedonia, Jamaica, Denver, and Italy Chapters.
Date and time: Thursday, February 25, 2021, at 9 am
Biography: Dr. Arslan (IEEE Fellow) has received his BS degree from Middle East Technical University (METU), Ankara, Turkey in 1992; MS and Ph.D. degrees in 1994 and 1998 from Southern Methodist University (SMU), Dallas, TX. USA. From January 1998 to August 2002, he was with the research group of Ericsson Inc., NC, USA, where he was involved with several projects related to 2G and 3G wireless communication systems. Since August 2002, he has been with the Electrical Engineering Dept. of University of South Florida, Tampa, FL, USA, where he is a Professor. In December 2013, he joined Istanbul Medipol University to found the Engineering College, where he has worked as the Dean of the School of Engineering and Natural Sciences. He has also served as the director of the Graduate School of Engineering and Natural Sciences in the same university. In addition, he has worked as a part-time consultant for various companies and institutions including Anritsu Company, Savronik Inc., and The Scientific and Technological Research Council of Turkey. Dr. Arslan’s research interests are related to advanced signal processing techniques at the physical and medium access layers, with cross-layer design for networking adaptivity and QoS control. He is interested in many forms of wireless technologies including cellular radio, wireless PAN/LAN/MANs, fixed wireless access, aeronautical networks, underwater networks, in vivo networks, and wireless sensors networks. His current research interests are on 5G and beyond radio access technologies, physical layer security, interference management (avoidance, awareness, and cancellation), cognitive radio, small cells, powerline communications, smart grid, UWB, multi-carrier wireless technologies, dynamic spectrum access, co-existence issues on heterogeneous networks, aeronautical (High Altitude Platform) communications, channel modeling and system design, and underwater acoustic communications. He has served as technical program committee chair, technical program committee member, session and symposium organizer, and workshop chair in several IEEE conferences. He is currently a member of the editorial board for the IEEE Surveys and Tutorials and the Sensors Journal. He has also served as a member of the editorial board for the IEEE Transactions on Communications, the IEEE Transactions on Cognitive Communications and Networking (TCCN), the Elsevier Physical Communication Journal, the Hindawi Journal of Electrical and Computer Engineering, and Wiley Wireless Communication and Mobile Computing Journal.
DETECT: Wearable Sensor Data to Predict COVID-19 and Viral Illnesses
Date and time: Tuesday, December 15, 2020, from 6 pm to 7:30 pm
Biography: Dr. Giorgio Quer received a Ph.D. degree (2011) in Information Engineering from University of Padova, Italy. In 2007, he was a visiting researcher at the Centre for Wireless Communication at the University of Oulu, Finland. During his Ph.D., he proposed a solution for the distributed compression of wireless sensor networks signals, based on the joint exploitation of Compressive Sensing and Principal Component Analysis. From 2010 to 2016, he was at the Qualcomm Institute, University of California San Diego (UCSD), working on cognitive networks protocols and implementation. At Scripps Research, he is leading the Data Science and Analytics Scripps team involved in the All of Us Research Program (NIH), together with several efforts involving big data and AI in digital medicine, including DETECT, towards the use of wearables to detect COVID-19. He is a Senior Member of the IEEE and a Distinguished Lecturer for the IEEE Communications society. His research interests include wireless sensor networks, probabilistic models, deep convolutional networks, wearable sensors, physiological signal processing, and digital medicine.
Current and Future Trends in 5G/B5G/6G
Presented by: Mehdi Bennis (U. Oulu) Walid Saad (VirginiaTech), Halim Yanikomeroglu (Carleton U), Wei Yu (U Toronto), and Vincent Wong (UBC)
Date and time: Monday, December 14, 2020, from 8:45 am to 12:15 pm
Event details and registration info: https://events.vtools.ieee.org/m/241334
Walid Saad, ECE Department, Virginia Tech, Blacksburg, USA
Professor, Fellow of IEEE
Title: Can Terahertz Communications Provide High-Rate Highly Reliable Low Latency Communications in 6G Networks?
Abstract: Communication at high-frequency terahertz (THz) bands is seen as a staple of the sixth generation (6G) of wireless cellular networks, due to the large amount of available bandwidth. However, 6G systems will have to support, not only high data rates, but also highly reliable communication links for emerging applications such as advanced wireless virtual reality (VR) systems. In particular, advanced wireless VR applications will impose new visual and haptic requirements that are directly linked to the quality-of-experience (QoE) of VR users. These QoE requirements can only be met by wireless 6G connectivity that offers high-rate and high-reliability low latency communications (HRLLC), unlike the low rates usually considered in vanilla 5G ultra-reliable low latency communication scenarios. Guaranteeing HRLLC in THz-enabled 6G systems requires dealing with the uncertainty that is specific to the THz channel. Therefore, in this talk, after a brief overview on our vision of 6G systems, we will explore the potential of THz for meeting HRLLC requirements. In this regard, we first quantify the risk for an unreliable VR performance through a novel and rigorous characterization of the tail of the end-to-end (E2E) delay. Then, we perform a thorough analysis of the tail-value-at-risk (TVaR) to concretely characterize the behavior of extreme wireless events crucial to the real-time VR experience. We use this analysis to derive system reliability for scenarios with guaranteed line-of-sight (LoS) as a function of THz network parameters. We then present simulation results that show how abundant bandwidth and low molecular absorption are necessary to improve the reliability, although their effect remains secondary compared to the availability of LoS, which significantly affects the THz HRLLC performance. We conclude our talk with an overview on other key open problems in the realms of THz communications and 6G systems.
Halim Yanikomeroglu, ECE Department, Carleton University, Ottawa, ON, Canada
Professor, Fellow of IEEE, Fellow of Canadian Academy of Engineering, Fellow of Engineering Institute of Canada
Title: Wireless Access Architecture: The Next 20+ Years
Abstract: Communication at high-frequency terahertz (THz) bands is seen as a staple of the sixth generation (6G) of wireless cellular networks, due to the large amount of available bandwidth. However, 6G systems will have to support, not only high data rates, but also highly reliable communication links for emerging applications such as advanced wireless virtual reality (VR) systems. In particular, advanced wireless VR applications will impose new visual and haptic requirements that are directly linked to the quality-of-experience (QoE) of VR users. These QoE requirements can only be met by wireless 6G connectivity that offers high-rate and high-reliability low latency communications (HRLLC), unlike the low rates usually considered in vanilla 5G ultra-reliable low latency communication scenarios. Guaranteeing HRLLC in THz-enabled 6G systems requires dealing with the uncertainty that is specific to the THz channel. Therefore, in this talk, after a brief overview on our vision of 6G systems, we will explore the potential of THz for meeting HRLLC requirements. In this regard, we first quantify the risk for an unreliable VR performance through a novel and rigorous characterization of the tail of the end-to-end (E2E) delay. Then, we perform a thorough analysis of the tail-value-at-risk (TVaR) to concretely characterize the behavior of extreme wireless events crucial to the real-time VR experience. We use this analysis to derive system reliability for scenarios with guaranteed line-of-sight (LoS) as a function of THz network parameters. We then present simulation results that show how abundant bandwidth and low molecular absorption are necessary to improve the reliability, although their effect remains secondary compared to the availability of LoS, which significantly affects the THz HRLLC performance. We conclude our talk with an overview on other key open problems in the realms of THz communications and 6G systems.
Vincent Wong, ECE Department, University of British Columbia, Vancouver, BC, Canada
Professor, Fellow of IEEE
Title: Throughput Optimization for Grant-Free Multiple Access with Multiagent Deep Reinforcement Learning
Abstract: Grant-free multiple access (GFMA) is a promising paradigm to efficiently support uplink access of Internet of Things (IoT) devices. In this talk, we present a deep reinforcement learning (DRL)-based pilot sequence selection scheme for GFMA systems to mitigate potential pilot sequence collisions. We formulate a pilot sequence selection problem for aggregate throughput maximization in GFMA systems with specific throughput constraints as a Markov decision process (MDP). By exploiting multiagent DRL, we train deep neural networks (DNNs) to learn near-optimal pilot sequence selection policies from the transition history of the underlying MDP without requiring information exchange between the users. While the training process takes advantage of global information, we leverage the technique of factorization to ensure that the policies learned by the DNNs can be executed in a distributed manner. Simulation results show that the proposed scheme can achieve an average aggregate throughput that is close to the optimum, and has a better performance than several heuristic algorithms.
Mehdi Bennis, ECE Department, University of Oulu, Finland
Professor, IEEE Fellow
Abstract: This talk will break down the vision of wireless network edge intelligence at scale in terms of theoretical and algorithmic principles in addition to a number of applications in beyond 5G/6G.
Wei Yu, ECE Department, University of Toronto, Toronto, ON, Canada
Fellow of IEEE and a Fellow of Canadian Academy of Engineering
Title: Data-Driven Approaches to Wireless Communication System Design
Abstract: In this talk, I will illustrate how machine learning can significantly improve the design of wireless communication systems. I will draw examples from scheduling and power control problems for wireless cellular networks to show that a data-driven approach can circumvent the need for accurate channel estimation and provide near optimal solutions to system-level optimization problems in wireless system design. I will also show how deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and multiuser precoding for massive MIMO systems, thereby providing an efficient solution to a distributed source coding problem. I will conclude by showing the benefit of data-driven design in term of robustness.
IEEE Seattle and Vancouver Joint Communications Chapter Virtual Holiday Party! With Dan Gelbart as a speaker
Event details and registration info: https://events.vtools.ieee.org/m/247150
Meeting link will be sent at least 2 days in advance of the event to all registrants.
This event is co-organized by IEEE Seattle and Vancouver Joint Communications Chapters.
Presented by: Dr. Dan Gelbart, Rapidia
Date and time: Friday, December 11, 2020, from 6 pm to 8 pm
Abstract: Heaviside and Kao are less known than Shannon and Hamming while their contribution to telecom is of the same magnitude. What was the contribution and how they achieved it makes a fascinating story. The talk will include showing some historical objects from Heaviside’s period.
Biography: Dan Gelbart is a well known Canadian inventor and entrepreneur. He has 128 US patents to his name and was a founder of several successful high tech companies in Canada. Cumulative revenues from these patents are several billion $. Dan was the co-founder of Creo, which revolutionized the printing industry by imaging printing plates thermally instead of photonically. Creo was sold to Kodak in 2005 for a billion $. Dan is also the co-founder of Kardium, a medical device company which has a treatment for atrial fibrillation showing much improved results compared to current treatments. Other successful companies based on technology developed by Dan were MDI (sold to Motorola) and Cymbolic Sciences (sold to Shlumberger). Currently Dan is the president of Rapidia, a company he founded to supply 3D printers for metals. Dan received numerous scientific awards, two honorary doctorates and won several crowd-sourced scientific competitions such as Innocentive. He also has a popular YouTube course on building prototypes. He has an MSc and BSc in Electrical Engineering from the Technion, Israel institute of Technology.
IEEE ComSoc Virtual Distinguished Lecture
Date and time: Monday, November 9, 2020, at 8 am
Abstract: Optimal resource allocation is a fundamental challenge for dense and heterogeneous wireless networks with massive wireless connections. Because of the non-convex nature of the optimization problems, often it is computationally demanding to obtain the optimal resource allocation. Machine learning, especially Deep learning (DL), is a powerful tool where a multi-layer neural network can be trained to model a resource management algorithm using network data. Therefore, resource allocation decisions can be obtained without intensive online computations which would be required otherwise for the solution of resource allocation problems. Recently, deep reinforcement learning (DRL) has emerged as a promising technique in solving non-convex optimization problems. Unlike deep learning (DL), DRL does not require any optimal/near-optimal training dataset which is either unavailable or computationally expensive in generating synthetic data. In this talk, I shall present a supervised DL-based as well as a centralized DRL-based downlink power allocation scheme for a multi-cell system intending to maximize the total network throughput. Specifically, I shall discuss a deep Q-learning (DQL) approach to achieve near-optimal power allocation policy. I shall present some simulation results to compare the proposed DRL-based power allocation scheme with the conventional schemes in a multi-cell scenario.
Biography: Ekram Hossain (F’15) is a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Canada. He is a Member (Class of 2016) of the College of the Royal Society of Canada. Also, he is a Fellow of the Canadian Academy of Engineering. Dr. Hossain’s current research interests include design, analysis, and optimization beyond 5G/6G cellular wireless networks. He was elevated to an IEEE Fellow “for contributions to spectrum management and resource allocation in cognitive and cellular radio networks”. To date, his research works have received 31,100+ citations (in Google Scholar, with h-index = 91). He received the 2017 IEEE ComSoc TCGCC (Technical Committee on Green Communications & Computing) Distinguished Technical Achievement Recognition Award “for outstanding technical leadership and achievement in green wireless communications and networking”. Dr. Hossain has won several research awards including the “2017 IEEE Communications Society Best Survey Paper Award” and the “2011 IEEE Communications Society Fred Ellersick Prize Paper Award”. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2017, 2018, and 2019. Currently he serves as the Editor-in-Chief of IEEE Press and an Editor for the IEEE Transactions on Mobile Computing. Previously, he served as the Editor-in-Chief for the IEEE Communications Surveys and Tutorials (2012-2016). He is a Distinguished Lecturer of the IEEE Communications Society and the IEEE Vehicular Technology Society. Also, he is an elected member of the Board of Governors of the IEEE Communications Society for the term 2018-2020.
IEEE ComSoc Virtual Distinguished Lecture
IEEE ComSoc Virtual Distinguished Lecture, organized by IEEE Seattle, Vancouver and Victoria ComSoc Chapters
Date and time: Wednesday, June 10, 2020, from 6 pm to 7:30 pm
Location: A Zoom meeting information invite will be sent to registrants.
Abstract: We are witnessing unprecedented growth in IoT, 5G and recently in AI. Collaboratively, these disruptive technologies will enable building smart capabilities in key markets health, mobility and public safety. As a result, a new class of services will be rolled out focusing on “personalization” in 2020 and beyond. Some potential scenarios will be presented and their impact on life and business.
The session is designed to inspire the audience, to creatively think, innovate and collaborate in defining what would be an early adoption use uses of personalized services that would be a differentiator for smart cities.
Three Takeaways
· Understand the key drivers and rapid growth and trends of IoT, 5G and AI as disruptive technologies.
· Power of collaborative technologies in enabling personalized services for smart cities.
· Examples of use cases leveraging disruptive technologies in key markets health, mobility and public safety for 2020 and beyond.
Fawzi is a senior member of IEEE, Distinguished Lecturer and IEEE ComSoc Regional Director for North America Board (2020-2021) and chairing of several society chapters (ComSoc, Signal Processing, Computer, EMB, Cons Elec.). Fawzi is the chair for WCNC 2022 and has organized several events such as smart city summit (2019), Blockchain for Healthcare (2018) and Greentech of Smart Cities (2018) and Advanced technologies in Healthcare (2017). Fawzi has been keynote speakers at international conferences and has several publications and co-authored book on “Collaborative Internet of Things for Future Smart Connected Life and Business” published by Wiley.
Fawzi holds a Bachelor of Science with honors and distinction; Masters in Computer Science and Executive MBA.
IEEE / UBC ECE Seminar
Date and time: Thursday, October 17, 2019, at 2 pm
Location: Room 418, Macleod Building, UBC, 2356 Main Mall, Vancouver, BC, Canada
Abstract: Automated management has been the holy grail of network management research for decades; it aims at achieving autonomous networks, i.e., networks capable to autonomously monitor their status, analyze problems, make decisions, and execute corrective actions. Despite several attempts to achieve autonomous networks in the past, their practical deployments have largely remained unrealized. Several factors are attributed to this, including the existence of many stakeholders with conflicting goals, reliance on proprietary solutions, the inability to process network monitoring data at scale, and the lack of global visibility restricting network-wide optimizations. The stars are now aligned to realize the vision of autonomous networks thanks to (i) advances in network softwarization; (ii) recent breakthroughs in machine learning; and (iii) the availability of large-scale data processing platforms. However, a number of challenges must be addressed in order to create the synergy between these different technology domains and achieve autonomous (a.k.a., self-driving networks) networks. This talk will discuss some of these challenges with particular focus on programmable network monitoring leveraging network softwarization, predictive machine learning for automated management decision making, and on-demand orchestration of network services.
Biography: Dr. Raouf Boutaba is a University Chair Professor of Computer Science at the University of Waterloo. He also holds an INRIA International Chair in France. He is the founding Editor in Chief of the IEEE Transactions on Network and Service Management (2007-2010), and the current Editor-in-Chief of the IEEE Journal on Selected Areas in Communications (JSAC). He served as the general or technical program chair for a number of international conferences including IM, NOMS and CNSM. His research interests are in the areas of network and service management. He has published extensively in these areas and received several journal and conference Best Paper Awards such as the IEEE 2008 Fred W. Ellersick Prize Paper Award. He also received other recognitions, including the Premier’s Research Excellence Award, Industry research excellence Awards, fellowships of the Faculty of Mathematics, of the David R. Cheriton School of Computer Science and several outstanding performance awards at the University of Waterloo. He has also received the IEEE Communications Society Hal Sobol Award and the IFIP Silver Core in 2007, the IEEE Communications Society Joe LociCero and the Dan Stokesbury awards in 2009, the Salah Aidarous award in 2012, the IEEE Canada McNaugthon Gold Medal in 2014, the Technical Achievement Award of the IEEE Technical Committee on Information Infrastructure and Networking as well as the Donald W. McLellan Meritorious Service Award in 2016. He served as a distinguished lecturer for the IEEE Computer and Communications Societies. He is fellow of the IEEE, a fellow of the Engineering Institute of Canada and a fellow of the Canadian Academy of Engineering.
IEEE Communications Society Distinguished Lecture
Date and time: Friday, October 18, 2019, at 11 am
Location: Room 418, Macleod Building, UBC, 2356 Main Mall, Vancouver
Abstract: Video content for streaming or downloading has the special property of a concentrated popularity distribution, i.e., a small percentage of all videos account for the vast majority of data traffic through wireless networks. Yet traditional wireless networks treat videos like any other files, transmitting them through unicast links. Over the past years, we have proposed and analyzed a new method of video transmission that is based on caching video files on user devices, and then distributing them on demand via spectrally efficient device-to-device (D2D) communications over short distances, thus converting (cheap) memory on the devices into bandwidth. This talk will give an overview of the method, and describe some of our more recent work that concentrated on information-theoretic scaling laws, analysis of popularity distribution based on large sets of measured data, and the tradeoff of energy efficiency and battery lifetime with network throughput.
Biography: Andreas F. Molisch is the Solomon Golomb – Andrew and Erna Viterbi Chair Professor at the University of Southern California. His research interest is wireless communications, with emphasis on wireless propagation channels, multi-antenna systems, ultrawideband signaling and localization, novel modulation methods, and caching for wireless content distribution. He is the author of four books, 20 book chapters, more than 250 journal papers, 340 conference papers, as well as 80 patents. He is a Fellow of the National Academy of Inventors, IEEE, AAAS, and IET, as well as Member of the Austrian Academy of Sciences and recipient of numerous awards, including the Sumner award of the IEEE and the Armstrong award of ComSoc.
IEEE / UBC ECE Seminar
Date and time: Friday, October 4, 2019, at 2 pm
Location: Room 418, Macleod Building, UBC, 2356 Main Mall, Vancouver
Abstract: Blockchain has emerged as a new ledger technology for data and transactions management. This decentralized ledger technology relies on consensus protocols and incentive mechanisms among a number of participants, i.e., miners and users, to achieve high data security and integrity. However, the participants are rational and will act according to their interests. As such, game theory appears to be a suitable tool to analyze and optimize the blockchain networks. In this talk, we will present the basics of game theory and review some typical game models such as non-cooperative game, hierarchical game, and evolutionary game that are adopted in blockchain. Then, the game formulations for mining pool management, computing resource allocation, and risk management in blockchain networks will be presented. Some research directions will be also discussed.
Biography: Dusit Niyato is currently a professor in the School of Computer Science and Engineering and, by courtesy, School of Physical & Mathematical Sciences, at the Nanyang Technological University, Singapore. He received B.E. from King Mongkuk’s Institute of Technology Ladkrabang (KMITL), Thailand in 1999 and Ph.D. in Electrical and Computer Engineering from the University of Manitoba, Canada in 2008. He has published more than 380 technical papers in the area of wireless and mobile networking, and is an inventor of four US and German patents. He has authored four books including “Game Theory in Wireless and Communication Networks: Theory, Models, and Applications” with Cambridge University Press. He won the Best Young Researcher Award of IEEE Communications Society (ComSoc) Asia Pacific (AP) and The 2011 IEEE Communications Society Fred W. Ellersick Prize Paper Award. Currently, he is serving as a senior editor of IEEE Wireless Communications Letter, an area editor of IEEE Transactions on Wireless Communications (Radio Management and Multiple Access), an area editor of IEEE Communications Surveys and Tutorials (Network and Service Management and Green Communication), an editor of IEEE Transactions on Communications, an associate editor of IEEE Transactions on Mobile Computing, IEEE Transactions on Vehicular Technology, and IEEE Transactions on Cognitive Communications and Networking. He was a guest editor of IEEE Journal on Selected Areas on Communications. He was a Distinguished Lecturer of the IEEE Communications Society for 2016-2017. He was named the 2017, 2018 highly cited researcher in computer science. He is a Fellow of IEEE.
IEEE / UBC ECE Seminar
Date and time: Monday, January 21, 2019, at 12 pm
Location: Room 418, Macleod Building, UBC, 2356 Main Mall, Vancouver
Abstract: Fibre optical communications underpin the transmission of global data traffic, supporting our information driven society and economy. However, as the demand for transmission capacity has been continuing to increase exponentially, the global fibre optic communication system (based on current technologies) will soon reach its limit, known as the Linear Capacity Limit. Such limit is due to the nonlinearity in optical fibres, which can significantly distort signals in a nonlinear fashion, especially when signal power is high. Recently, a novel solution to incorporate fibre nonlinearity into the communication model has been introduced based on Nonlinear Fourier Transform (NFT). In this approach, fibre dispersion and nonlinearity are incorporated when defining the independent nonlinear modes in the NFT domain that propagate through the fibre without any distortion. Analysis has suggested that this NFT based approach does not suffer the same fibre nonlinearity-induced limitation as in conventional systems (where data rate will peak and decay as power increases beyond a threshold).These evidence suggest that NFT is a very promising approach to cope with nonlinearities and to achieve transmission capacity beyond linear capacity limit. In this talk, we will discuss such a new NFT based transmission systems and identify some challenges that it faces.
Biography: Terence Chan completed his PhD in 2001. He was an Assistant Professor at The Chinese University of Hong Kong in 2001. From February 2002 to June 2004, he was a Post-doctoral Fellow in the Department of Electrical and Computer Engineering at the University of Toronto. In 2004, he became an Assistant Professor at the Department of Computer Science in University of Regina, Canada. He is now an Associate Professor in Institute for Telecommunications Research at the University of South Australia. His expertise is in the areas of information theory and communications networks. Some highlights of his work include the characterization of the relation between information inequalities and group theoretic inequalities, the proof for the equivalence of characterization of network coding capacity region and the cone of all entropy functions and sub-optimality of linear network codes. In the past few years, he has focused on the area of fibre optical communications based on nonlinear Fourier transform.