Upcoming YP Seminar Details:
Recently, simultaneous wireless information and power transfer (SWIPT) using radio frequency (RF) waves has drawn an upsurge of research interest in various areas of communications, signal processing, and networking. SWIPT is considered as promising technology for practical energy-limited applications such as wireless sensor networks, wireless body networks, low-powered devices, internet of things (IoT), etc. Also, in the next generation wireless systems such as 5G, wireless RF energy harvesting is considered to be a promising solution to the energy scarcity issue. In the literature, SWIPT has been generally studied under the ideal (and unrealistic) assumption of linear energy harvesting, which means that the energy (or power) conversion efficiency of the energy harvesting circuit is constant over the infinitely wide range of the input RF power. However, as validated in many field measurements, the energy conversion efficiency of the actual energy harvesting circuit highly depends on the input RF power level. Specifically, due to the nonlinearities of the practical diode such as the turn-on voltage and saturation issue, the linearity assumption of the energy harvesting circuitry is significantly deviated in practical situations. In this talk, we present the recent research results on SWIPT considering the nonlinear energy harvesting. In particular, we will talk about the fundamental performance limit of SWIPT in terms of rate-energy (R-E) trade-off, the approach of using multiple energy harvesting circuits, mode selection between energy harvesting and information transfer, and optimal dynamic power allocation for SWIPT.
Il-Min Kim received the B.S. degree in electronics engineering from Yonsei University, Seoul, Korea, in 1996, and the M.S. and Ph.D. degrees in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST), Taejon, Korea, in 1998 and 2001, respectively. From October 2001 to August 2002 he was with the Dept. of Electrical Engineering and Computer Sciences (EECS) at Massachusetts Institute of Technology (MIT), Cambridge, USA, and from September 2002 to June 2003 he was with the Dept. of Electrical Engineering at Harvard University, Cambridge, USA, as a Postdoctoral Research Fellow. In 2003, he joined the Dept. of Electrical and Computer Engineering at Queen’s University, Kingston, Canada, and he is currently a Professor. His research interests include machine (deep) learning for various systems (especially with sensors), IoT (and IoE), signal processing for IoT, (mobile) crowd sensing, fog/cloud networks, communication security, blockchain for wireless communications, physical layer security, energy harvesting and SWIPT, compressive sensing, military communications and Radars, and 5th generation (5G) and beyond 5G wireless communications systems. He holds a number of patents either issued or pending in U.S., Japan, Germany, and Korea.
In recent years, there has been an increasing interest in aerial (airborne) networks. The domain is
very broad and includes (but not limited to) the connectivity and networking of aerial users (ex:
cargo/delivery drones), as well as aerial BSs (UAV-/drone-BSs), high-altitude platforms (HAPs),
very low earth orbit (VLEO) satellites, flying ad hoc networks (FANETs), and VHetNets (vertical
heterogeneous networks); enabling technologies such as machine learning for autonomous
operation, free-space optical communications, network slicing, and energy harvesting are
of paramount importance in this emerging framework. This workshop presents the current
research on connected and autonomous aerial networks. It is supported by IEEE Ottawa Young
Professionals. Many of the speakers are IEEE Young Professionals including PhD candidates and
researchers. This workshop also falls within the scope and goals of the IEEE Future Networks
- 10:00 am – 4:30 pm, Thursday, 07 February 2019
- The Maker Lab, 4463 ME (Mackenzie Building), Systems and Computer Engineering, Carleton University
- Lunch will be provided; Sponsored by IEEE Young Professionals.
- Arrival: 10:00-10:15 am
- Morning Session: 10:15 am – 12:00 pm
- Session Chair: Dr. Sahar Aghajanzadeh
- Connected and Autonomous Aerial Networks in 2030s
- Dr. Halim Yanikomeroglu, Professor / Carleton
- Adaptive Routing in Flying Ad Hoc Networks
- Dr. Burak Kantarci, Professor / uOttawa
- Cellular-Connected UAV in Integrated Aerial and Terrestrial Networks
- Nesrine Cherif, PhD candidate / uOttawa & Carleton
- Session Chair: Dr. Sahar Aghajanzadeh
- Lunch: 12:00 pm – 1:30 pm
- The Caf – Carleton University, Residence Commons, 3rd floor
- The Caf – Carleton University, Residence Commons, 3rd floor
- Afternoon Session I: 1:30 – 2:45 pm
- Session Chair: Dr. Jalal Khamse-Ashari
- Integrated Terrestrial-Nonterrestrial Wireless Access in Beyond-5G Networks
- Mohamed Alzenad, PhD candidate / Carleton
- Space-Air-Ground Networks: Challenges and Opportunities
- Dr. Wael Jaafar, NSERC PDF / Carleton
- FSO (Free-Space Optical) Communications Opportunities in Aerial Networks
- Dr. Sahar Aghajanzadeh, Research Associate / Carleton
- Coffee Break: 2:45 – 3:15 pm
- Afternoon Session II: 3:15 – 4:30 pm
- Session Chair: Dr. Wael Jaafar
- Aerial Coverage in Cellular Networks
- Dr. Jordan Melzer, Senior Engineer, Technology Strategy / TELUS
- Beamforming Techniques in Aerial Networks
- Hossein Vaezy, Visiting Researcher / Carleton & PhD candidate / IUT, Iran
- A Look into 3GPP Release-16 from the Perspective of Aerial Networks
- Irem Bor-Yaliniz, PhD candidate / Carleton & Network Design Engineer / Huawei Canada Research Centre
Workshop Sponsored by: IEEE Young Professionals
Systems and Computer Engineering Carleton University
Workshop Chair: Dr. Halim Yanikomeroglu, Professor, Carleton
Co-Organized and Sponsored by IEEE Ottawa Young Professionals Affinity Group.
Arrival: 9:30 – 10:00 am
Morning Session: 10:00 am – 12:00 noon
Keynote Speech (abstract and bio at the end)
Exploration Strategy in Wireless Systems with Reinforcement Learning
Dr. Haris Gacanin, Department Head, Nokia Bell Labs, Belgium
AI/ML-based Security and Trust in Mobile Services
Dr. Burak Kantarci, Professor, uOttawa
Lunch: 12:15 – 1:45 pm
The Caf – Carleton University, Residence Commons, 3rd floor
Afternoon Session I: 2:00 – 3:00 pm
Threat of Adversarial Attacks on Machine Learning in Network Security
Kunle Ibitoye, PhD candidate, Carleton, and Rana Abou Khamis, MASc candidate, Carleton
(Supervisors: Professors Ashraf Matrawy and Omair Shafiq, Carleton)
Resource Allocation with Deep Reinforcement Learning for Microgrid Communications
Dr. Melike Erol-Kantarci, Professor, uOttawa, and Medhat Alsayed, PhD candidate, uOttawa
Coffee Break: 3:00 – 3:30 pm
Afternoon Session II: 3:30 – 4:30 pm
Wireless Network Personalization: Why it Matters and How to Approach It
Rawan Alkurd, PhD candidate, Carleton
(Supervisors: Professors Ibrahim Abualhaol and Halim Yanikomeroglu, Carleton)
Machine Learning for Wireless Networks: Applications to Routing and Resource Management
Dr. Thomas Kunz, Professor, Carleton
We are now several years into explosion of machine learning (ML) in wireless networks, used to enrich decision-making by finding structures in data – knowledge discovery – as means to describe the user behavior and network performance. With new designs of wireless networks, complexity and dynamicity rises, network resources are scattered and diversity of network elements increases. Consider these examples with interesting challenges: 1) massive number of Internet-of-Things devices, sensors and actuators give rise to the problem of dynamic network planning; 2) broadband wireless leads to problems with real-time radio resource management; 3) ultra-reliable communications require support of real-time adjustments on latency and reliability in the orders of 99,99999%. For such designs artificial intelligence (AI) is expected to support high adaptability with respect to wireless environment and its services (e.g. virtual reality).
This talk discusses a paradigm shift from contemporary data-driven wireless with ML toward autonomous wireless with AI. We explore motivation, opportunities and methodology to adopt training-free AI methods for self-organization of wireless systems. We point out specific properties of wireless environment and classify future directions on training-free vs training-based systems. We start from popular data-driven ML techniques and briefly elaborate their benefits and shortcomings for wireless application mentioned above. The main focus is on reinforcement learning as a major (training-free) representative of AI. We briefly discuss learning principles of intelligent agent with problem of random exploration for wireless-specific environment. We discuss principles of self-organization by synthesizing reasoning and learning with knowledge management. Finally, we end with a case study using wireless AI prototype for self-deployment and self-optimization. The talk provokes new coming challenges and unveil interesting future directions across multi-disciplinary research areas.
Haris Gačanin received his Dipl.-Ing. degree in Electrical engineering from University of Sarajevo in 2000. In 2005 and 2008, respectively, he received MSc and PhD from Tohoku University in Japan. He worked at Tohoku University until 2010 as Assistant Professor and joined Alcatel-Lucent (now Nokia) in 2010, where he established research on data-driven analysis of communication systems at physical and media access layers. Currently, he is department head at Bell Labs and adjunct teaching professor at KU Leuven. His professional interests relate to research confluence between artificial intelligence and physical-layer communications to establish autonomous wireless systems. He has 200+ scientific publications (journals, conferences and patens) and invited/tutorial talks. He is senior member of IEEE and IEICE and recipient of IEICE Communication Systems Best Paper Award (joint 2014, 2015, 2017), The 2013 Alcatel-Lucent Award of Excellence, the 2012 KDDI Foundation Research Award, the 2009 KDDI Foundation Research Grant Award, the 2008 JSPS Postdoctoral Fellowships for Foreign Researchers, the 2005 Active Research Award in Radio Communications, 2005 Vehicular Technology Conference (VTC 2005-Fall) Student Paper Award from IEEE VTS Japan Chapter and the 2004 Institute of IEICE Society Young Researcher Award. He was awarded by Japanese Government (MEXT) Research Scholarship in 2002.
Admission: Free. Registration required.
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GaN HEMT has been a focus in both academia and industry, due to the extremely low figure of
merits (RDS(on) x QG) compared with conventional Silicon counterparts. The opportunities, challenges and design considerations for GaN HEMTs in industrial and automotive applications will be presented in the device/packaging and system perspectives. Design examples are detailed to show how the system
performance maximization is enabled by GaN HEMTs with minimum cost in the selected applications.
The key design procedures will be thoroughly discussed, i.e., topology selection, loss analysis, cost reduction, power stage layout, thermal design, etc.
This presentation is aimed at covering the fundamentals as well as the latest research and updates of GaN HEMTs applications. The target audience is the design engineers, researchers, graduate/undergraduate
students interested in industrial/automotive applications or just GaN technology.
Juncheng (Lucas) Lu received B.S. degree from Zhejiang University, Hangzhou, China, and M.S. degree from Kettering University, Michigan, USA. He was a research engineer with Delta Power Electronics Center, Shanghai, China. Since 2016, he has been with GaN Systems, Inc., Ottawa, Canada. He manages the head office applications and is responsible for Americas and EMEA application support. His research interest is wide bandgap devices application, power electronics packaging, high-efficiency high power
density power supply, and electric vehicle battery charger. He published more than 20 IEEE/SAE transaction and conference papers and holds 9 U.S. Patents.
|Risk Management (RM) is a process that provides
confidence that planned objectives will be achieved.
The focus of this seminar will be (1) Defining the risk management and
Speaker: Dr. Ola Abdrabou
Visiting Professor, the Infrastructure Protection and Security (IPIS) Program-