IEEE Winnipeg Section

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Archive for the ‘Communications Chapter’ Category

IEEE Communications Society Seminar – August 14, 2018

Tuesday, July 31st, 2018

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IEEE COMMUNICATIONS SOCIETY, Winnipeg Section, and Department of Electrical and Computer Engineering, University of Manitoba, are hosting the following technical seminar.

You are welcome to attend.

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TITLE: Stable Throughput Regions of Opportunistic NOMA and Cooperative NOMA with Full-Duplex Relaying

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SPEAKER: Dr. Vincent Wong

DATE:   Tuesday, 14 August 2018

TIME:     10:00 am

PLACE: E1-270, EITC, University of Manitoba, Fort Garry Campus

ORGANIZER: IEEE Communications Society (Winnipeg Section)

ENTRANCE FEE: Free

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ABSTRACT:

Non-orthogonal multiple access (NOMA) is a spectrally efficient multiple access technique, which has the potential to meet the rapidly increasing traffic demand of the fifth generation (5G) wireless networks. With NOMA, multiple users can be simultaneously served by the same base station via exploiting the power domain in addition to the time and frequency domains. However, by sharing the frequency channel and transmit power among the paired NOMA users, NOMA may not always achieve better performance than orthogonal multiple access (OMA). In this talk, the basic idea of NOMA transmission is discussed. For downlink NOMA transmission with dynamic traffic arrival for spatially random users, two variants of NOMA schemes, namely opportunistic NOMA and cooperative NOMA with full-duplex relaying, are proposed to enhance the stable throughput region, which is characterized by using tools from queuing theory and stochastic geometry.  Results show that the sum rates of the proposed NOMA schemes over OMA are higher when users having more diverse target data rates are paired.

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BIOGRAPHY OF THE PRESENTER:

Vincent Wong is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia. His research areas include protocol design, optimization, and resource management of communication networks, with applications to the Internet, wireless networks, smart grid, mobile cloud computing, and Internet of Things. Dr. Wong is an Editor of IEEE Transactions on Communications and an Associate Editor of IEEE Transactions on Mobile Computing. He has served as a guest editor of IEEE Journal on Selected Areas in Communications and IEEE Wireless Communications. Dr. Wong is a Fellow of the IEEE.

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For additional information, please contact:

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Jun Cai, Ph.D., P.Eng.

Chair, IEEE Communications Society Chapter, IEEE Winnipeg Section

Professor

Department of Electrical and Computer Engineering

University of Manitoba

Winnipeg, MB Canada R3T 5V6

Email: jun.cai@umanitoba.ca

Telephone: 1-204-4746419

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IEEE Communications Society Seminar – August 10, 2018

Tuesday, July 31st, 2018

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IEEE COMMUNICATIONS SOCIETY, Winnipeg Section, and Department of Electrical and Computer Engineering, University of Manitoba, are hosting the following technical seminar.

You are welcome to attend.

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TITLE: Novel Chirp Spread Spectrum Methods for Low-Power Wide-Area Networks

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SPEAKER: Dr. Ha Nguyen

DATE:   Friday, 10 August 2018

TIME:     10:00 am

PLACE: E1-270, EITC, University of Manitoba, Fort Garry Campus

ORGANIZER: IEEE Communications Society (Winnipeg Section)

ENTRANCE FEE: Free

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ABSTRACT:

Low-power wide-area networks (LPWANs) have recently emerged as a promising communication technology for the Internet of Things (IoT). LPWANs are designed to achieve large coverage ranges, extend battery lifetimes of end-devices, and reduce the operational cost of traditional cellular networks. By exploiting the unlicensed, industrial, scientific, and medical (ISM) frequency band and transmitting small packets at low data rates, these networks can be operated with very low reception sensitivities. The long-range and low-power properties of LPWANs make these networks an interesting candidate for smart sensing technology in civil infrastructures as well as in industrial applications.

This talk first introduces the chirp spread spectrum (CSS) technique used in low-power wide-area networks known as LoRa. Then it presents novel approaches to modulate and demodulate LoRa signals with high implementation efficiency, flexibility and excellent performance. The last part of the talk explains a method to exploit the phase information of CSS signals to encode extra information bits, leading to throughput improvement of the conventional CSS system.

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BIOGRAPHY OF THE PRESENTER:

Dr. Ha Nguyen received the B.Sc. degree from Hanoi University of Technology (HUT), Vietnam, in 1995, the M.Sc. degree from the Asian Institute of Technology (AIT), Thailand, in 1997, and the Ph.D. degree from the University of Manitoba in 2001, all in electrical engineering. He joined the Department of Electrical and Computer Engineering, University of Saskatchewan in 2001, and became a Professor in 2007. He currently holds the position of NSERC/Cisco Industrial Research Chair in Low-Power Wireless Access for Sensor Networks. His research interests fall into broad areas of Communication Theory, Wireless Communications, and Statistical Signal Processing.

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For additional information, please contact:

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Jun Cai, Ph.D., P.Eng.

Chair, IEEE Communications Society Chapter, IEEE Winnipeg Section

Professor

Department of Electrical and Computer Engineering

University of Manitoba

Winnipeg, MB Canada R3T 5V6

Email: jun.cai@umanitoba.ca

Telephone: 1-204-4746419

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IEEE Communications Society Seminar – November 24, 2017

Tuesday, October 31st, 2017
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IEEE COMMUNICATIONS SOCIETY, Winnipeg Section, and Department of Electrical and Computer Engineering, University of Manitoba, are hosting the following technical seminar.
All are welcome to attend.
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TITLE: Massive Device Connectivity with Massive MIMO

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SPEAKER:  Dr. Wei Yu
DATE:    Friday, 24 November 2017
TIME:      2:30 pm
PLACE:     Room E2-160, EITC, University of Manitoba, Fort Garry Campus
ORGANIZER:  IEEE Communications Society (Winnipeg Section)
ENTRANCE FEE: Free
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ABSTRACT:
Massive connectivity is a key requirement for future 5G wireless access. This talk considers a massive device communications scenario in which a large number of devices need to connect to a base-station, but user traffic is sporadic so that at any given coherence time only a subset of users are active. For such a system, user activity detection and channel estimation are key issues. This talk first provides an information theoretical analysis for massive connectivity by illustrating how the cost of user identification and channel estimation affects the achievable degree-of-freedom. Next, we present a two-phase framework in which compressed sensing techniques are used in the first phase to identify the devices and their channels, while data transmission takes place in the second phase. We propose the use of approximate message passing (AMP) for device identification and show that state evolution can be used to analytically characterize the missed detection and false alarm probabilities in AMP. This talk further considers the massive connectivity problem in the massive MIMO regime. We analytically show that massive MIMO can significantly enhance user activity detection, but the non-orthogonality of pilot sequences can nevertheless introduce significant channel estimation error, hence limiting the overall rate. We quantify this effect and characterize the optimal pilot length for massive uncoordinated device access.
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BIOGRAPHY OF THE PRESENTER:
Wei Yu (S’97-M’02-SM’08-F’14) received the B.A.Sc. degree in Computer Engineering and Mathematics from the University of Waterloo, Waterloo, Ontario, Canada in 1997 and M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, Stanford, CA, in 1998 and 2002, respectively. Since 2002, he has been with the Electrical and Computer Engineering Department at the University of Toronto, Toronto, Ontario, Canada, where he is now Professor and holds a Canada Research Chair (Tier 1) in Information Theory and Wireless Communications. His main research interests include information theory, optimization, wireless communications and broadband access networks. Prof. Wei Yu currently serves on the IEEE Information Theory Society Board of Governors (2015-17). He served as an Associate Editor for the IEEE Transactions on Information Theory (2010-2013), and currently serves as an Area Editor for the IEEE Transactions on Wireless Communications. He currently chairs the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society. Prof. Wei Yu received a Journal of Communications and Networks Best Paper Award in 2017, a Steacie Memorial Fellowship in 2015, an IEEE Communications Society Best Tutorial Paper Award in 2015, an IEEE ICC Best Paper Award in 2013, an IEEE Signal Processing Society Best Paper Award in 2008, and an Early Career Teaching Award from the Faculty of Applied Science and Engineering, University of Toronto in 2007. He is recognized as a Highly Cited Researcher. Prof. Wei Yu is a Fellow of IEEE and a Fellow of Canadian Academy of Engineering.
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For additional information, please contact:
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Jun Cai, Ph.D., P.Eng.
Chair, IEEE Communications Society Chapter, IEEE Winnipeg Section
Associate Professor
Department of Electrical and Computer Engineering
University of Manitoba
Winnipeg, MB Canada R3T 5V6
Telephone: 1-204-4746419
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IEEE Communications Society Seminar – October 26, 2017

Monday, October 16th, 2017
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IEEE COMMUNICATIONS SOCIETY, Winnipeg Section, and Department of Electrical and Computer Engineering, University of Manitoba, are hosting the following technical seminar.
All are welcome to attend.
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TITLE: Time-Sensitive Networking (TSN) – A topic on Industrial Ethernet
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SPEAKER:  Dr. Guillaume Mantelet
DATE:    Thursday, 26 October 2017
TIME:      1:00 pm
PLACE:     Room E3-262, EITC, University of Manitoba, Fort Garry Campus
ORGANIZER:  IEEE Communications Society (Winnipeg Section)
ENTRANCE FEE: Free
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ABSTRACT:

Deterministic Ethernet aims at filling the gap left by the IEEE802.1Q standard to proprietary solutions (e.g. CAN buses), regarding soft and hard real-time applications. Ethernet was first thought to be probabilistic by nature in order to provide reliability and fairness for accessing to the medium. However, the unpredictable delivery of Ethernet frames may lead to unwanted loss, delay and jitter in streams, with potentially disastrous consequences on life-critical applications – one cannot accept a smart car controller freezing, waiting for a delayed sample coming from a sensor.

In this presentation, we will discuss Deterministic Ethernet, and Time-Sensitive Networking and show how with an accurate Timing and Synchronization protocol (IEEE802.1AS), a Time-Aware scheduler (IEEE802.1Qbv) can ensure the tight time-delivery of frames. Also, we will talk about drafts and future concepts of TSN, such as the frame preemption (IEEE802.1Qbu). Practical use cases and a review of the state-of-the-art tools will be provided to achieve determinism in an existing network.
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BIOGRAPHY OF THE PRESENTER:

Dr. Guillaume Mantelet has been working in Embedded Software Engineering at Iders – a GE Transportation company, since 2015. He received his M.Sc. in Telecommunications and Network Engineering (2007) and Ph.D in Electrical Engineering (2012) at Ecole de Technologie Superieure in Montreal. Before joining Iders, he worked as a Software Quality Assurance Specialist at Accedian Networks (2012).

Dr. Mantelet’s core expertise is “layer 2” oriented, and includes the establishment of end-to-end paths in optical transmission lines, and the definition of a control plane, Carrier Ethernet and more specifically, concepts touching the Quality of Service in Ethernet networks, and more recently Deterministic Ethernet. Starting with a scientific training, he could leverage his knowledge by developing tools in embedded projects.
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For additional information, please contact:
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Jun Cai, Ph.D., P.Eng.
Chair, IEEE Communications Society Chapter, IEEE Winnipeg Section
Associate Professor
Department of Electrical and Computer Engineering
University of Manitoba
Winnipeg, MB Canada R3T 5V6
Telephone: 1-204-4746419
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IEEE Communications Society Seminar – A Probabilistic Theory of Deep Learning – May 18, 2017

Thursday, May 11th, 2017
Event Title: Technical Seminar – A Probabilistic Theory of Deep Learning
Speaker: Dr. Richard Baraniuk
Date: Thursday May 18, 2017
Time: 2:00 pm
Location: Room E3-262 , EITC, University of Manitoba, Fort Garry Campus
Abstract: A grand challenge in machine learning is the development of computational algorithms that match or outperform humans in perceptual inference tasks that are complicated by nuisance variation. For instance, visual object recognition involves the unknown object position, orientation, and scale in object recognition while speech recognition involves the unknown voice pronunciation, pitch, and speed. Recently, a new breed of deep learning algorithms have emerged for high-nuisance inference tasks that routinely yield pattern recognition systems with near- or super-human capabilities. But a fundamental question remains: Why do they work? Intuitions abound, but a coherent framework for understanding, analyzing, and synthesizing deep learning architectures has remained elusive. We answer this question by developing a new probabilistic framework for deep learning based on the Deep Rendering Model: a generative probabilistic model that explicitly captures latent nuisance variation. By relaxing the generative model to a discriminative one, we can recover two of the current leading deep learning systems, deep convolutional neural networks and random decision forests, providing insights into their successes and shortcomings, a principled route to their improvement, and new avenues for exploration.
Biography of the Speaker: Richard G. Baraniuk is the Victor E. Cameron Professor of Electrical and Computer Engineering at Rice University.  He received the B.Sc. degree in 1987 from the University of Manitoba, the M.Sc. degree in 1988 from the University of Wisconsin-Madison, and the Ph.D. degree in 1992 from the University of Illinois at Urbana-Champaign, all in Electrical Engineering.  His research interests lie in  new theory, algorithms, and hardware for sensing, signal processing, and machine learning.  He is a Fellow of the American Academy of Arts and Sciences, National Academy of Inventors, American Association for the Advancement of Science, and IEEE.  He has received the DOD Vannevar Bush Faculty Fellow Award (National Security Science and Engineering Faculty Fellow), the IEEE Signal Processing Society Technical Achievement Award, and the IEEE James H. Mulligan, Jr. Education Medal.  He holds 28 US and 4 foreign patents that have been licensed to 2 companies.
Other information: The seminar is free and open to all who wish to attend. For more information please contact Dr. Jun Cai.