IEEE Technical Seminar by Melike Erol-Kantarci

IEEE Technical Seminar
This event is co-organized by IEEE Seattle Section Joint Chapter, IEEE Vancouver Joint Communications Chapter, and IEEE Victoria Section Joint Chapter.
 
Title: AI-Enabled Wireless Networks
 
Presented by: Prof. Melike Erol-Kantarci, University of Ottawa
 
Date and time: May 20, 2021, from 12 pm to 1 pm
 
Event details and registration info: https://events.vtools.ieee.org/m/270829 
Abstract: Future wireless networks are expected to support a multitude of services demanded by Enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low-latency Communications (uRLLC), and massive Machine Type Communications (mMTC) users. Heterogeneous devices with different quality of service (QoS) demands will require intelligent and flexible allocation of network resources in response to network dynamics. To meet these demands, future wireless networks must incorporate a paradigm shift in network resource optimization, in which efficient and intelligent resource management techniques are employed. Artificial intelligence, or more specifically machine learning algorithms stand as promising tools to intelligently manage the networks such that network efficiency, reliability, robustness goals are achieved and QoS demands of users are satisfied. In this talk, we will provide an overview of the state-of-art in machine learning algorithms and their applications to wireless networks, in addition to their challenges and the open issues in terms of their applicability to various functions of future wireless networks.
Biography: Melike Erol-Kantarci is Canada Research Chair in AI-enabled Next-Generation Wireless Networks and Associate Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She is a Faculty Affiliate at the Vector Institute, Toronto, and the Institute for Science, Society and Policy at University of Ottawa. She has over 150 peer-reviewed publications which have been cited over 5500 times and she has an h-index of 39. She has received numerous awards and recognitions. Recently, she received the 2020 Distinguished Service Award of the IEEE ComSoc Technical Committee on Green Communications and Computing and she was named as N2Women Stars in Computer Networking and Communications in 2019. Dr. Erol-Kantarci has delivered 50+ keynotes, tutorials and panels around the globe and has acted as the general chair and technical program chair for many international conferences and workshops. Her main research interests are AI-enabled wireless networks, 5G and 6G wireless communications, smart grid and Internet of things. She is an IEEE ComSoc Distinguished Lecturer, IEEE Senior member and ACM Senior Member.

IEEE VDL Talk by Feifei Gao

IEEE VDL Talk by Feifei Gao
IEEE Virtual Distinguished Lecturer (VDL) Talk, co-organized by the IEEE Kingston Section Chapter, Quebec Section Joint Chapter, IEEE Vancouver Joint Communications Chapter, and other chapters.
Title: Deep Learning for Physical Layer Communications: An Attempt towards 6G
Presented by: Prof. Feifei Gao, Tsinghua University, China

Date and time: May 18, 2021, from 5 pm to 6:30 pm

Event details and registration info: https://events.vtools.ieee.org/m/271566 
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.
Bio: 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.

IEEE VDL Talk by Shiwen Mao

IEEE Virtual Distinguished Lecturer (VDL) Talk, co-organized by the IEEE New York Section Chapter, North New Jersey Section Joint Chapter, IEEE Vancouver Joint Communications Chapter, and other chapters.

TitleRFID for Human Activity Sensing: Challenges, Solutions and Applications 
Presented byProf. Shiwen Mao, Auburn University

Date and time: Sunday, May 2, 2021, at 5 pm (PDT)
Event details and registration info: https://events.vtools.ieee.org/m/265684 
 
AbstractWith the rapid development of radio frequency (RF) sensing in the Internet of Things (IoT), human activity sensing, detection and tracking have attracted increasing attention. Among the various RF sensors, radio-frequency identification (RFID) has its unique advantages of low-cost, small form factor, battery-free, and robustness to surrounding interference. Beyond its original use of responding stored Electronic Product Code (EPC) data when interrogated by a reader, RFID tags can be used as wearable sensors on the human body. In this talk, we will investigate the various technical challenges on fully exploiting RFID for human activity recognition and tracking, such as frequency hopping, and the noisy and sparse RFID data, and examine potential solutions. We will then review several of our recently works on RFID based human vital sign monitoring, drowsy driving detection, and 3D human pose monitoring and tracking. We will conclude this talk with thoughts on future work in the area.
Biography: Shiwen Mao received his Ph.D. in electrical engineering from Polytechnic University, Brooklyn, NY. He held the McWane Endowed Professorship from 2012 to 2015 and the Samuel Ginn Endowed Professorship from 2015 to 2020 in the Department of Electrical and Computer Engineering at Auburn University, Auburn, AL. Currently, he is a professor and Earle C. Williams Eminent Scholar Chair, and Director of the Wireless Engineering Research and Education Center (WEREC) at Auburn University. His research interest includes wireless networks, multimedia communications, and smart grid. He is a Distinguished Lecturer of IEEE Communications Society, and is on the Editorial Board of IEEE TWC, IEEE TNSE, IEEE TMC, IEEE IoT, IEEE OJ-ComSoc, IEEE/CIC China Communications, IEEE Multimedia, IEEE Networking Letters, and ACM GetMobile, among others. He received the IEEE ComSoc TC-CSR Distinguished Technical Achievement Award in 2019 and NSF CAREER Award in 2010. He is a co-recipient of the IEEE Vehicular Technology Society 2020 Jack Neubauer Memorial Award, the 2004 IEEE Communications Society Leonard G. Abraham Prize in the Field of Communications Systems, and several conference best paper awards. He is a Fellow of the IEEE.

IEEE Technical Seminar by Ibrahim Gedeon of TELUS

IEEE Technical Seminar, co-organized by the IEEE Seattle Joint ComSoc/VT/BT/IT/ITS Chapter and IEEE Vancouver Joint Communications Chapter

Title5G Roll-Out at TELUS 
Presented byIbrahim Gedeon of TELUS

Date and time: Thursday, April 22, 2021, at 6 pm
Event details and registration info: https://events.vtools.ieee.org/m/268416 
 
AbstractAttendees will learn about the TELUS 5G roll-out and the assumed use cases. Ibrahim will also share his thoughts on where 5G standards need to go in order to deliver on the customer-centric view of 5G. He will also speak to the roles that MEC and ORAN play – two critical elements that must be considered by an operator moving from 5G coverage to true 5G services.
Biography: Ibrahim Gedeon is one of the global telecommunications industry’s eminent thought leaders. He has carved out an international career by combining insight and skill as an applied scientist with a lighthearted approach to leadership. As Chief Technology Officer for TELUS, a leading national telecommunications company in Canada, he is responsible for all technology development and strategy, security, service and network architecture, service delivery and operational support systems, as well as service and network convergence, and network infrastructure strategies and evolution. Under his leadership the TELUS wireless broadband network has become one of the best in the world. Ibrahim serves on the board of the Next Generation Mobile Networks Alliance, the Alliance for Telecommunications Industry Solutions and the Institute for Communication Technology Management. In addition to his industry leadership roles, he has been awarded with IEEE Communications Society’s prestigious Distinguished Industry Leader Award and elected a Fellow of the Canadian Academy of Engineering (CAE) for his significant contributions to the field of engineering. Ibrahim has also been named one of the 100 most powerful and influential people in the telecoms industry in Global Telecoms Business magazine’s GTB Power 100. Ibrahim holds a Bachelor’s degree in Electrical Engineering from the American University of Beirut, a Master’s in Electronics Engineering from Carleton University and an Honourary Doctor of Laws degree from the University of British Columbia and is passionate about supporting engaged, high-performing teams.

IEEE Technical Seminar (Dr. Charlie Jackson)

IEEE Technical Seminar, co-organized by the IEEE Seattle Joint ComSoc/VT/BT/IT/ITS Chapter, IEEE Seattle AP/ED/MTT Joint Chapter, and IEEE Vancouver Joint Communications Chapter

TitleEngineering Musical Woodwind Instruments with 3D Printing
Presented byDr. Charlie Jackson of Northrop Grumman Aerospace Systems

Date and time: Thursday, March 11, 2021, at 6 pm
Event details and registration info: https://events.vtools.ieee.org/m/263567 
 
AbstractPeople have been making musical instruments for a long time; for over 40,000 years. We use whatever we can find to make them. Today we can use 3D printers to make them. This talk will show how to apply microwave theory (transmission line theory, network analysis, and S-Parameters) to the design of woodwind instruments; especially renaissance instruments such as the flute, crumhorn, or cornetto. The talk will then show how to use 3D printing to make working instruments.
BiographyDr. Charlie Jackson has had an interest in the design of woodwind instruments for many years. He has written articles on Quasi-optical components, High Temperature Superconductors for microwave applications, Ferroelectric phase shifters, and Microwave Radiometers. He has been awarded three patents. He is on the Center Staff of the RFMS of Northrop Grumman Aerospace Systems. He was President of the IEEE Microwave Theory and Techniques Society in 2001, and is a Fellow of the IEEE.

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.

Title: Physical Layer Security and Wireless Security
Presented by: Prof. Huseyin Arslan, University of South Florida

Date and time: Thursday, February 25, 2021, at 9 am
Event details and registration info: https://events.vtools.ieee.org/m/262308 
WebEx link will be sent the night before the event to all registrants.

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

Presented by: Dr. Giorgio Quer, Scripps Research 

Date and time: Tuesday, December 15, 2020, from 6 pm to 7:30 pm
Event details and registration infohttps://events.vtools.ieee.org/m/248181
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.
Abstract: The availability of large longitudinal data opens new opportunities exploiting statistical learning and deep convolutional neural networks in healthcare. We will overview our large study with data collected from wireless devices from 200,000 individuals for 2 years. We will observe how sleep changes significantly among this large population and is related to age and body mass index. We will also show how a person’s resting heart rate may be a uniquely individualized measure of their health, with potential value for early detection of important physiologic changes. This large study provides the baseline for DETECT, our app-based, nationwide clinical study enrolling individuals who routinely use a smartwatch or other wireless devices to determine if individualized tracking of changes in heart rate, activity and sleep can provide early diagnosis and self-monitoring for COVID-19. In this talk, we discuss how this program has been implemented and which insights for the individual and for public health are obtained by analyzing data from more than 36,000 individuals. We show our recent results on the validation of this algorithm, proving that it can identify COVID-19 positive cases by analyzing both self-reported symptoms and wearable sensor data.

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 infohttps://events.vtools.ieee.org/m/241334

Meeting link will be sent at least 2 days in advance of the event to all registrants.
This event is co-organized by IEEE Montreal, Ottawa, Turkey, Toronto Young Professionals Affinity Groups, and IEEE Vancouver Joint Communications Chapter.
IEEE Young Professionals Affinity Groups of the Montreal Section, Ottawa Section, Toronto Section, Turkey Section, and the IEEE Vancouver Joint Communications Chapter bring bright minds from the flagship research groups across the globe to give the community technical lectures on cutting-edge areas in wireless communications. This event will cover broad arrays of topics along with fundamental research results targeting a variety of applications in 5G/B5G/6G.

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?

AbstractCommunication 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

AbstractCommunication 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

AbstractGrant-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

AbstractThis 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

AbstractIn 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 infohttps://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.

Title: Oliver Heaviside and Charles Kao

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

IEEE ComSoc Virtual Distinguished Lecture, co-organized by the IEEE Atlanta, Vancouver, Italy, Windsor, North Macedonia, Egypt, Pune, and Galveston Bay Chapters
Title: Wireless Systems Design in the Beyond 5G Era: Promises of Deep Learning and Deep Reinforcement Learning
Presented by: Prof. Ekram Hossain, University of Manitoba

Date and time: Monday, November 9, 2020, at 8 am
Event details and registration infohttps://events.vtools.ieee.org/m/242882
Meeting link will be sent at least 2 days in advance of the event to all registrants.

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.