IEEE Winnipeg Section

IEEE

Archive for the ‘Communications Chapter’ Category

IEEE Communications Society Seminar – November 24, 2017

Tuesday, October 31st, 2017
==========================================================================
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

TITLE: Massive Device Connectivity with Massive MIMO

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
For additional information, please contact:
=================================================================
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
==================================================================

IEEE Communications Society Seminar – October 26, 2017

Monday, October 16th, 2017
==========================================================================
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
TITLE: Time-Sensitive Networking (TSN) – A topic on Industrial Ethernet
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
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.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
For additional information, please contact:
=================================================================
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
==================================================================

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.

Communications Chapter Seminar – Waveforms and Coding Methods for New Radio in 5G

Friday, January 27th, 2017

==========================================================================
IEEE COMMUNICATIONS SOCIETY, Winnipeg Section, is hosting the following technical seminar.

You are welcome to attend.

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
TITLE: Waveforms and Coding Methods for New Radio in 5G
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

SPEAKER: Dr. Nandana Rajatheva

DATE: Tuesday, 31 January 2017

TIME: 1:30 pm

PLACE: Room EITC E2-160, EITC, University of Manitoba, Fort Garry Campus

ORGANIZER: IEEE Communications Society (Winnipeg Section)

ENTRANCE FEE: Free

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
ABSTRACT:
Cellular systems are expected to employ higher frequencies going into mmWaves. Given this there are justifications to consider different waveforms than the well known OFDM especially in massive MIMO scenarios. Therefore we have considered the performance of single carrier schemes in a variety of channel configurations including peak-to-average power ratio (PAPR) issues. In addition as the standardization is going on in 5G within 3GPP, various channel coding methods have been analyzed in terms of their block and bit error rates. We consider Turbo, LDPC and Polar codes as the main schemes. These are investigated with respect to the suitable rates, block lengths by proper design for comparison.
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

BIOGRAPHY OF THE PRESENTER:
Nandana Rajatheva (SM’01) received the B.Sc. degree in Electronics and Telecommunication engineering (with first-class honors) from the Universityof Moratuwa, Moratuwa, Sri Lanka, in 1987 and the M.Sc. and the Ph.D. degrees from the University of Manitoba, Winnipeg, MB, Canada, in 1991 and 1995, respectively. He is an Adjunct Professor at the Centre for Wireless Communications, University of Oulu, Finland. His research interests include waveforms and channel coding for 5G and resource allocation for cellular systems as well as smart grid communications. He worked in several European and Finnish projects such as METIS related to the development of 5G. Dr. Rajatheva is a Senior Member of the IEEE Communications and Vehicular Technology Societies.

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

For additional information, please contact:
=================================================================
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
Email: jun.cai@umanitoba.ca
Telephone: 1-204-4746419
==================================================================

Communications Chapter Seminar

Thursday, February 28th, 2013

2013-03-06-com

Title:

Two-Stage Face Recognition using Global and Local Features

Date:

Wednesday, March 6, 2013 at 2:20 pm.

Location:

Room E2-125, EITC, University of Manitoba, Fort Garry Campus

Speaker:

Dr. Ekta Walia Bhullar
Department of Computer Science
South Asian University
New Delhi, India

Contact:

For questions or more information: Pradeepa Yahampath 204-474-8784.