T1: Connected Vehicles

Presented by: Shahrokh Valaee, University of Toronto

Time: 9:00–12:30
Room: Casson

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Abstract—Today’s vehicles are equipped with a plurality of microprocessors and microcontrollers, which in some models easily exceeds one hundred. Adding to this immense processing power, various sensing capabilities, unlimited battery lifetime, and large body for placement of multiple antennas and sensors, make today’s vehicles very powerful sensing and computing machines. We are witnessing the emergence of Self-Driving Vehicles, which intend to be an assistant to, or completely replace, the driver. Unfortunately, we also notice the accidents that such autonomous vehicles are involved in. Researchers, engineers, and government entities are investigating whether autonomous driving will be able to address all the needs for a safe driving experience.

In this tutorial, we will show that autonomous driving alone will not be able to remove accidents on roads and will indeed be the start of a new chapter for auto industry that will pave the path for the more advanced Connected Vehicles technology. A connected vehicle communicates with its immediate and extended neighbourhood and becomes an important node in a smart environment. This tutorial discusses the various technologies that are the potential enabler of connected vehicles and smart cities.

Tutorial Objectives
From the three pillars of sensing, computing, and communication—for becoming a cognitive node— our vehicles are well equipped with the former two, but significantly deprived of the last pillar. Despite much progress in manufacturing of sophisticated vehicles, the communication methods among drivers on roads are primitive, through visual contact; rear lights turning on to warn a breaking situation. Autonomous driving addresses some of these issues by using advance sensing to enhance safety. However, sensing quickly loses its effectiveness in high speeds, severe weather conditions, and non-line-of-sight. In a recent tragedy, a Tesla car failed to detect a truck and crashed into it resulting in a fatal accident. Most of such accidents can be prevented if wireless communication and networking devices are installed in cars that allowed vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But, what is the most appropriate communication technology that can be used in cars and also be attractive for future buyers?

The next generation car buyers are the tweeter and facebook generation. For them, the most attractive feature is not the engine horsepower, rather the capability for onboard social networking and continuous connection to their social group. Are our roads and vehicles ready for digital dashboards and social networks? What is the technology that can support such applications? Can 5G and the WAVE technology coexist? In this tutorial, we will review the techniques and the challenges for cooperative communication in Connected Vehicles. We will discuss all layers in the communication stack including, applications, WAVE short messaging, IEEE1609 and IEEE802.11p suite of standards, security, and the requirement of 5G to support vehicular networks. We will also discuss research challenges in vehicular communication and networking including safety-aware communication, congestion control, topology variation, high velocity, and network agility.

This tutorial will discuss communication technologies that are appropriate for connected vehicles. It will discuss the contending technologies that will be the enablers of vehicular communications and networking. The attendees will learn about network requirements for safe driving, sensing and communication, needs for V2V and V2X communication, IEEE and ISO standards, visible light communication, mm-Wave in vehicular communication, high-speed WiFi and 5G systems.
The tutorial will also discuss the open research problems in Connected Vehicles.

Tutorial Outline

• Safe driving in vehicular environment
• Sensing and communication
• Vehicle Infrastructure Integration
• Medium Access in V2V and V2I
• DSRC/WAVE Technology
• ISO and CALM standards
• IEEE and SAE standards
• Visible light communication
• mm-Wave in vehicular environment
• Emerging high-speed WiFi
• 5G for V2X communication
• Open research problems and challenges

Primary Audience
The primary audience of this tutorial are researchers from both academia and industry who are interested in Connected Vehicles, which includes R&D engineers for vehicular networking and safety systems and academic researchers and graduate students who are interested in learning about the current state of research in the area. There is no special background required, except for familiarity with communications and networking. The tutorial will review the necessary background.

Novelty
This tutorial will discuss the most recent advancements in the field and will illustrate the R&D needed for the next generation of intelligent vehicles. The topics will include WiFI, 5G, visible light , mm-wave. Multi-antenna high-speed WiFi communication is actively pursued in IEEE standardization efforts. The 5G wireless communications is under much attention in industry and academia. Communication via visible lights, as an alternative solution for communication in vehicular environment, is emerging as a contending technology. The availability of mmWaves for communication will raise the possibility for new applications.

Biography
Shahrokh Valaee is a Professor in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto. He is the founder and the Director of the Wireless and Internet Research Laboratory (WIRLab) at the University of Toronto. Professor Valaee is the Lead TPC Chair of PIMRC 2017, and has served as Networks Track Co-Chair of WCNC 2015, TPC Co-Chair of ICT 2014, Tutorial Chair of PIMRC2014, Co-Chair of the Wireless Networks Track of WPMC 2012, and the TPC chair of PIMRC 2011, among other conference chairing activities. He has served as an Editor of IEEE Transactions on Wireless Communications, and IEEE Signal Processing Letters, and as a guest editor for several journals including IEEE Wireless Communications Magazine, Wiley Journal on Wireless Communications and Mobile Computing, and EURASIP Journal on Advances in Signal Processing. He is currently serving as an Editor of Journal of Computer and System Science and the Area Editor of Localization and Location Based Services of Springer Encyclopaedia of Wireless Networks. Professor Valaee is a Fellow of the Engineering Institute of Canada. His research includes, vehicular networks, localization and tracking, and cellular systems.

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T2: Vehicular Communications and 5G Paradigm - Vision and Practices

Presented by: Dr. Muhammad Alam: Instituto de Telecomunicações, University of Aveiro, Portugal

Time: 14:00–17:30
Room: Osgoode East

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Abstract—Transportation systems play an extremely important role in modern society and effective vehicular connectivity techniques can significantly enhance efficiency of travel, reduce traffic incidents and improve safety, alleviate the impact of congestion; devising the so-called Intelligent Transportation Systems (ITS) experience. While some of the enabling technologies are entering their mature phase, e.g., traffic flow sensors, IEEE 802.11p and ETSI ITS G5, there is still the need of a complete integrated solution that can take the most benefits from a real-time analysis of the data gathered and appropriate reaction on the transportation system. The closed loop interaction between vehicles, drivers and the transportation infrastructure puts more pressure on the research community to tackle the challenges and requirements of future mobility. The plethora of new application areas of Intelligent Transportation Systems has raised concern about the inter-connectivity of future vehicles. For instance, many ITS services have time-lines constraints that are not fulfilled by the communication protocols proposed so far, specifically in road congestion and accident scenarios. Further, the technology choice for vehicular communication has raised more concerns – which technology to use for vehicular communications? 3GPPP committee has launched efforts to study the feasibility of LTE-based services for vehicular communication and connected vehicles are being considered a relevant part of the future 5G ecosystem. Therefore, this tutorial covers the existing standards for vehicular communications in a critical manner and presents a comprehensive overview of future mobility envisioned in 5G.

Tutorial Objectives
The main objectives are to present:
• A comprehensive overview of 5G vision for smart mobility
• A comprehensive overview of existing market status for Vehicular communications
• Technical overview of IEEE 802.11p
• Technical overview of LTE-V and 3GPP vision
• An analysis of the end user requirements
• An analysis of the automotive industries practices
• Real-time safety application for road safety (technology choice)
• Real-time requirements of safety applications
• Presentation of the technologies from real-time perspectives
• Developing road safety applications (Methodology)
• Deployment challenges, Laws and regulations - Political aspects

Tutorial Outline

1. Introduction
2. 5G Vision for Future Mobility
   1. Expectations
   2. Timeline
3. Existing Technology choices for vehicular communications
   1. Overview
4. IEEE 802.11p
   1. Introduction
   2. Technical overview
5. 3GPP LTE-V
   1. Introduction
   2. Technical overview
6. A unified solution
   1. Existing projects
   2. Future proposals and directions
7. Market overview
   1. Automotive industry
   2. End users
   3. Challenges
   4. Are we on the right track?
8. Road Safety
   1. The Technology choice
   2. Existing practices
   3. Applications development for Road Safety (eCall etc.)
9. Conclusions

Primary Audience
The intended audience of this tutorial are:
• Undergraduate Students
• Graduate Students
• Researchers
• Faculty member (Computer science, Engineering)
• Automotive industry
• Application developers

Novelty
1. 5G vision focuses only on Vehicular communication
2. Will cover both IEEE 802.11p and LTE-V
3. The first ever comparison between the two in tutorial format
4. Market overview – Automotive industries, telecom, end users
5. Real-time vehicular communications aspects for future road safety
6. Real-time application development for for future road safety

Biography
Muhammad Alam (Ph.D., Senior Researcher) holds a PhD degree in computer science from University of Aveiro, Portugal (2013-14). In 2009, he joined the Instituto de Telecomunicações - Aveiro (Portugal) as researcher and completed his Ph.D from University of Aveiro with a specialization in Inter Layer and Cooperative Design Strategies for Green Mobile Networks. He has participated in several European Union FP7 projects such as Hurricane, C2POWER, ICSI, PEACE and Portuguese government funded projects such SmartVision. Currently, he is working as senior researcher at Instituto de Telecomunicações and participating in European Union and Portuguese government funded projects. His research interests include IoT, Real-time wireless communication, 5G, Vehicular networks, Context-aware systems and Radio resource management in next generation wireless networks. He is the editor of Book “Intelligent Transportation Systems, Dependable Vehicular Communications for Improved Road Safety”. He is the author of several journal and conference publications as well as book chapters. He is also the TPC member and reviewer for a number of reputed conferences, journals, and magazines. He is IEEE and IEEE IES member. He served as general co-chair of future 5V conference and also served as session chairs in a number of reputed conferences such as IEEE IECON 2016, IEEE WFCS 2016, IEEE ITSC 2015. He also provided his services as guest editor to several journals.

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T3: Flexible Radio Access Beyond 5G: A Future Projection

Presented by: Hüseyin Arslan, University of South Florida

Time: 9:00–12:30
Room: Osgoode East

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Abstract—Today's wireless services and systems have come a long way since the rollout of the conventional voice-centric cellular systems. The demand for wireless access in voice and multi-media applications has increased tremendously. In addition to these, new application classes like extreme mobile broadband communication, ultra reliable and low latency communications, massive machine type communications, and Internet of Things have gained significant interest recently for 5G. The trend on the variety and the number of mobile devices along with the mobile applications will certainly continue beyond 5G, creating a wide range of technical challenges such as cost, power efficiency, spectrum efficiency, extreme reliability, low latency, robustness against diverse channel conditions, cooperative networking capability and coexistence, dynamic and flexible utilization of wireless spectrum. In order to address these technical challenges, 5G waveforms and radio access technologies (RATs) should be much more flexible. The current 4G systems rely on the orthogonal frequency multiple access (OFDM) waveform, which is not capable of supporting the diverse applications that 5G and beyond will offer. This is because the traffic generated by 5G and beyond is expected to have radically different characteristics and requirements when compared to current wireless technology. For 5G to succeed, numerous waveform alternatives have been explored to best meet its various technical requirements. However, none of the alternatives were able to address all the requirements at the same time.

Tutorial Objectives
During the standardization of 5G, one thing has become certain: there is no single enabling technology that can achieve all of the applications being promised by 5G networking. This will be even more pronounced beyond 5G. For this purpose, the concept of using multiple OFDM numerologies, i.e., different parameterization of OFDM based subframes, within the same frame has been proposed in 3GPP discussions for 5G. This concept will likely meet the current expectations in multiple service requirements to some extent. However, since it is almost obvious that quantity of wireless devices, applications, and heterogeneity of user requirements will keep increasing towards the next decade(s), the sufficiency of the aforementioned flexibility level remains quite disputable considering future expectations. Therefore, novel RATs facilitating much more flexibility are needed to address the aforementioned technical problems.

In this tutorial, we will discuss the potential directions to achieve further flexibility in RATs beyond 5G. In this context, a framework for developing flexible waveform, numerology, and frame design strategies will be discussed along with sample methods in this direction. We will also discuss their potential role to handle various issues in the upper system layers.

Tutorial Outline

• Channel and waveform
• Application and waveform
• Introduction to OFDM and Multi-Carrier Modulation
• OFDM advantages and problems
• Adaptive, Flexible & Cognitive OFDM
• Other Important Waveforms (SC-FDE, SC-FDMA, DFT-s-OFDM,
• UW-OFDM etc. )
• Numerology and OFDM (OFDM variants from OFDM baseline)
• Future concepts in Waveform:
  • mmWave waveform design (SC versus MC in mmWave)
  • Hybrid waveforms
  • Flexible waveforms
  • Non-orthogonal waveform design
  • Differential modulation (non-coherent modulation) in OFDM (minimal pilot OFDM design)
  • PHY security in OFDM (secure OFDM design)

Primary Audience
This tutorial is intended for technical professionals in the communications industry, technical managers, and researchers in both academia and industry. Therefore, the key audience for the tutorial is: graduate students (Master or PhD), postdoctoral scholars, researchers, faculty members, scientists, and engineers in academia as well as in the public and private sectors in the broad area of wireless telecommunications.

Novelty
In this tutorial, we will discuss the potential directions to achieve further flexibility in RATs beyond 5G. In this context, a framework for developing flexible waveform, numerology, and frame design strategies will be discussed along with sample methods in this direction. We will also discuss their potential role to handle various issues in the upper system layers.

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 at 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 Quality of Service (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, 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, in vivo 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, etc

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T4: Error Correction Coding for 5G and Beyond: Design Requirements and Target Technologies

Presented by: Prof. Stark Draper, Dr. Nuwan Ferdinand, Edward S. Rogers Sr. Department of Electrical and Computer

Time: 14:00–17:30
Room: Governor General Parlor Room

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Abstract—In the first half of this tutorial we will introduce the audience to the basics of the two families of error correction codes standardized for 5G cellular systems: LDPC codes and Polar codes. The emphasis will be on developing foundational knowledge of the code families and basic decoding algorithms as well as the advantages, disadvantages, and limitations of each family. The emphasis will be on developing understanding through illustrative numerical comparisons. In the second half of the tutorial we will consider three important application areas: in 5G, in vehicle-to-vehicle communications, and in the Internet-of-things. We will introduce each application area in the context of the novel challenges it presents to error correction technology, the design requirements, and the degree to which LDPC and Polar codes stack up. By the end of the tutorial the audience will have a broad sense of what error correction coding can now deliver, and what it must deliver beyond 5G.

Tutorial Objectives
In the first half of the tutorial we will introduce the audience to the error correction coding (ECC) families standardized for 5G:

1. LDPC codes and Polar codes. The audience will learn and understand the following:
1a. The definition of each family of codes.
1b. What are the basic encoding and decoding algorithms to the level needed by a system designer.
1c. The various code construction used in practice (and standardized, e.g., quasi-cyclic), the decoding algorithms used (sum-product and min-sum belief propagation decoding for LDPC and successive cancellation and list decoding for Polar codes).
1d. The above constructions and algorithms in the context of the attainable tradeoffs between rate, reliability, throughput, decoding complexity, and versatility of each family of codes.
1e. The advantage, the disadvantage, and the limitations of each family through illustrative numerical comparisons.
1f. The “sweet spot” for each family.
1g. How to select a class of codes to use in the context of the design requirements of a specific application of interest.

In the second half of the tutorial the focus will shift to three emerging areas of application: 5G, vehicle-to-vehicle, and IoT, the design requirements of each application, and how each code family stacks up.

2. 5G systems
2a. The audience will first receive a high-level intro to 5G.
2b. Assuming the audience is most familiar with 5G we will move straight to design requirements. • Specific requirements include: the need to achieve 10Gbps peak throughput, flexible encodings/decoders to support a wide range of communications rates and block lengths, the need for high order modulation for high-SNR and high-rate communications.

3. Vehicle-to-vehicle communications
3a. The audience will first receive a high-level intro to vehicle-to-vehicle communications.
3b. We will discuss the application requirements that ECC need to support, and will how coding might be designed to work in conjunction with other methods to meet these requirements (e.g., coding at PHY layer + ARQ vs coding only).
3c. Specific requirements include: block length, rate adaptability, (ultra high) reliability, low latency. LDPC and Polar codes will be compared according to these measures.

4. IoT applications
4a. The audience will first receive a high-level intro to IoT applications
4b. We will discuss what is IoT by discussing the extreme breadth of both spatial scale (human / area / industrial / municipal) and of time temporal scale (hours / min / sec / msec) of possible IoT applications.
4c. We will discuss how such heterogeneity introduces new demands for flexibility, efficiency, reliability, and responsiveness, contrasting with contemporary systems.
4d. Specific requirements include: short block lengths (e.g., in M2M communications), infrequent transmission of small amounts of data (e.g., in sensor networks), low-cost and low-power and ease of deployment, scalable coding strategies to support massive numbers of sensors, support for mission critical communications requiring ultra-reliability and low latency. LDPC and Polar codes will be compared according to these measures.

5. In the concluding part of the tutorial, the audience will learn about future challenges for error correction coding beyond 5G.

Tutorial Outline

1. Intro (10 min)
2. Coding theory (80 min)
   1. LDPC (40min)
      1. Definition of ensemble
      2. Visualization using factor graph
      3. Illustrative iterative decoding using the BEC
      4. Illustrate decoding for more general channels -- BSC, AWGN, fading channels – using numerical results
      5. Discussion of attainable performance: BER vs SNR, error floor, Shannon limit at infinite and finite block lengths, power consumed in decoding
      6. Implementation aspects: quasi-cyclic codes, decoding algorithms beyond the BEC (min-sum and sum-product), high-order modulation (BICM, MLC)
   2. Polar (40 min)
      1. The polarization phenomenon – coding is easy if channel is noiseless or useless, polarization drives virtual channels to those two extremes
      2. Definition of the ensemble and visualization
      3. Illustrative successive cancellation decoding using BEC
      4. Illustrate decoding for more general channels – BSC, AWGN, fading channels – using numerical results
      5. Discussion of attainable performance, same fundamental limits as before, power consumed in decoding
      6. Implementation aspects: algorithms beyond the BEC, list decoding, high-order modulation
3. Applications (80 min)
   1. 5G (30 min)
      1. Intro to 5G and its demands
      2. Design challenges of 5G for ECC
      3. How LDPC and polar codes fits in 5G
      4. How to support multiple rates and block lengths
      5. Practical approaches to high order modulation
   2. Vehicle-to-vehicle (25 min)
      1. Intro to vehicle-to-vehicle communication
      2. Demands and restrictions in designing ECC
      3. How to design ultra-reliable and low latency error correction systems
   3. IoT (25 min)
      1. Intro to IoT
      2. Design challenges and limitations
      3. How to design low power and low cost codes
      4. Role of short block length codes
4. Wrap-up (10 min)

Primary Audience
The target profile of audiences are system designers and researchers (students and other academics) who want to learn how to leverage recent developments in error correction coding to support 5G, V2V, and IoT applications. No prior knowledge of error correction coding is expected. We anticipate some industrial practitioners familiar with ECC may attend, especially those interested in learning about LDPC codes, Polar codes and challenges in the three application areas discussed.

Novelty
We will present the latest developments in error correction coding in the context of 5G, vehicle-to-vehicle and IoT. These future communication networks require thousand folds gain over current standards. This introduces new sets of challenges for future approaches to ECC to provide high data rates, low latency, and ultra-reliability. We will provide a comprehensive tutorial how these requirements can be met leveraging the latest development in coding theory.

Biography
STARK DRAPER is an Associate Professor of ECE at the University of Toronto and was an Associate Professor at the University of Wisconsin, Madison. His industrial work on error correction includes developing codes for Mitsubishi Electric’s optical transport networks, and licensing a novel L3 cache design to Intel Corp. As a research scientist he has worked at the Mitsubishi Electric Research Labs (MERL), Disney’s Boston Research Lab, Arraycomm Inc., the C. S. Draper Laboratory, and Ktaadn Inc. He completed postdocs at the University of Toronto and at the University of California, Berkeley. He received the M.S. and Ph.D. degrees from the Massachusetts Institute of Technology (MIT), and the B.S. and B.A. degrees in Electrical Engineering and in History from Stanford University. His research interests include communications and information theory, error-correction coding, statistical signal processing and optimization, security, as well as the application of these disciplines to computer architecture.

Dr. Draper has received the NSERC Discovery Award, the NSF CAREER Award, the 2010 MERL President's Award, and teaching awards from the UofT, UW-Madison, and MIT. He received an Intel Graduate Fellowship, Stanford’s Frederick E. Terman Engineering Scholastic Award, and a U.S. State Department Fulbright Fellowship. He is a member of the IEEE Information Theory Society Board of Governors.

NUWAN FERDINAND is a postdoctoral fellow of Department of Electrical and Computer Engineering at the University of Toronto. He received his PhD degree, in the field of Telecommunication engineering, at the Centre for Wireless Communications, the University of Oulu, Finland in 2016. His research interests are communication theory, coding theory and their applications in communication networks. His recent research results include practical lattice codes for communication networks and coding to speed up machine learning algorithms.

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T5: Stochastic Geometry-Based Modeling and Analysis of 5G Cellular Networks

Presented by: Ekram Hossain, IEEE Fellow, Professor, University of Manitoba, Canada

Time: 9:00–12:30
Room: Governor General Parlor Room

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Abstract—Recently, stochastic geometry models have been shown to provide tractable and accurate performance bounds for cellular wireless networks including multi-tier and cognitive cellular networks, underlay device-to-device (D2D) communications, energy harvesting-based communication, coordinated multipoint transmission (CoMP) transmissions, full-duplex (FD) communications, etc. These technologies will enable the evolving fifth generation (5G) cellular networks. Stochastic geometry, the theory of point processes in particular, can capture the location-dependent interactions among the coexisting network entities. It provides a rich set of mathematical tools to model and analyze cellular networks with different types of cells (e.g., macro cell, micro cell, pico cell, or femto cell) with different characteristics, in terms of several key performance indicators such as SINR coverage probability, link capacity, and network capacity. This tutorial will provide an extensive overview of the stochastic geometry modeling approaches for next-generation cellular networks, and the state-of-the-art research on this topic. After motivating the requirement for spatial modeling for the evolving 5G cellular networks, the basics of stochastic geometry modeling tools and the related mathematical preliminaries will be discussed. Then, a comprehensive survey on the literature related to stochastic geometry models for single-tier as well as multi-tier and cognitive cellular networks and underlay D2D communications will be presented. Then, a taxonomy of the stochastic geometry modeling approaches based on the target network model, the point process used, and the performance evaluation technique will be discussed.

Tutorial Objectives
For more than three decades, stochastic geometry has been used to model large-scale ad hoc wireless networks, and develop tractable models to characterize and better understand the performance of these networks. Recently, stochastic geometry models have been shown to provide tractable and accurate performance bounds for cellular wireless networks including multi-tier and cognitive cellular networks, underlay device-to-device (D2D) communications, energy harvesting-based communication, coordinated multipoint transmission (CoMP) transmissions, full-duplex (FD) communications, etc. These technologies will enable the evolving fifth generation (5G) cellular networks. Stochastic geometry, the theory of point processes in particular, can capture the location-dependent interactions among the coexisting network entities. It provides a rich set of mathematical tools to model and analyze cellular networks with different types of cells (e.g., macro cell, micro cell, pico cell, or femto cell) with different characteristics (i.e., transmission power, cognition capabilities, etc.) in terms of several key performance indicators such as SINR coverage probability, link capacity, and network capacity. For the analysis and design of interference avoidance and management techniques in such multi-tier cellular networks (which are also referred to as small cell networks or HetNets), rigorous yet simple interference models are required. However, interference modeling has always been a challenging problem even in the traditional single-tier cellular networks.

The aim of this tutorial is to provide an extensive overview of the stochastic geometry modeling approach for next-generation cellular networks, and the state-of-the-art research on this topic. After motivating the requirement for spatial modeling for the evolving 5G cellular networks, it will introduce the basics of stochastic geometry modeling tools and the related mathematical preliminaries. Then, it will present a comprehensive survey on the literature related to stochastic geometry models for single-tier as well as multi-tier and cognitive cellular wireless networks, underlay D2D communication, and cognitive and energy-harvesting D2D communication. It will also present a taxonomy of the stochastic geometry modeling approaches based on the target network model, the point process used, and the performance evaluation technique. Finally, it will discuss the open research challenges and future research directions.

The learning outcomes are:

1. Enabling technologies for the evolving 5G cellular networks
2. Requirement for spatial modeling of 5G networks and different modeling approaches
3. Basics of point processes and interference modeling in large-scale wireless networks
4. Taxonomy of existing techniques for SINR modeling and performance evaluation in cellular networks
5. Stochastic geometry modeling of large-scale single and multi-tier cellular networks (HetNets)
6. Stochastic geometry modeling of cognitive small cells in HetNets
7. Stochastic geometry modeling of model selection and power control for D2D communications
8. Open research problems in stochastic geometry modeling of cellular networks

Tutorial Outline

Overview of 5G Cellular Networks and Spatial Modeling Techniques

Multi-tier cellular networks, cognitive cellular and D2D communication, energy harvesting-based communication

Network design and operation cycle

Key performance indicators (KPIs): SINR outage/coverage, average rate, transmission capacity

SINR modeling techniques

Stochastic geometry modeling

Point Process and Interference Modeling

Point processes (PPP, clustered processes, repulsive processes)

Campbell theorem and probability generating functional

Neyman Scott process: Matern cluster process and modified Thomas cluster process

Laplace transform of the pdf of interference

Performance Evaluation Techniques

Technique #1: Rayleigh fading assumption

Technique #2: Region bounds and dominant interferers

Technique #3: Fitting

Technique #4: Plancherel-Parseval theorem

Technique #5: Inversion

Modeling Large-Scale Single and Multi-Tier Cellular Networks

Modeling downlink transmissions

Modeling uplink transmissions

Single-tier networks with frequency reuse

Biasing and load balancing

Optimal deployment of BSs

Large-scale multiple-input multiple-output cellular systems

Modeling Cognitive Small Cells in Multi-Tier Cellular

Networks

Spectrum sensing range and spectrum reuse efficiency

Spectrum access schemes by cognitive small cells

Network modeling

Outage probability (channel outage and SINR outage) analysis for downlink transmissions in cognitive small cells

Modeling Mode Selection and Power Control for Underlay D2D Communication

Biasing-based mode selection and channel inversion power control for underlay D2D communication

Network modeling and stochastic geometry analysis

Cognitive and energy harvesting-based D2D communication

Network modeling and stochastic geometry analysis

Open Issues and Future Research Directions

Primary Audience
This tutorial will be of interest to graduate students, researchers, and engineers from both the communications and networking community who are interested in modeling and analysis of next-generation cellular wireless networks (including multi-tier/small cell networks/HetNets, D2D communication, and cognitive radio systems)

Novelty
The topic is very timely. With increasing interest in the use of stochastic geometry tools for performance modeling and analysis of large-scale cellular wireless networks (which is quite evident from the recent publications in different IEEE journals and conferences), the tutorial is expected to attract a good crowd of attendees.

Biography
Ekram Hossain (F'15) is currently a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Winnipeg, Canada. His current research interests include modeling, design, and analysis of wireless networks with emphasis on 5G cellular networks, cooperative and cognitive wireless systems, and green radio communications. He is an author/editor of several books in these areas. He was selected as a Distinguished Lecturer of the IEEE Vehicular Technology Society for the term 2016-2017.

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T6: Spectrum Access Ecosystem: Dynamic Radio Spectrum Access as a Service by Keivan Navaie, Associate Professor, Lancaster University has been cancelled

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T7: Software Defined Infrastructures for Big Sensed Data in the IoT

Presented by: Amr El Mougy (German University in Cairo, Egypt) and Mohamed Ibnkahla (Carleton University, Canada)

Time: 9:00–12:30
Room: Fitzgerald

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Abstract—The Internet of Things (IoT) envisions a world where everyday objects are transformed into smart entities using sensors/actuators and technologies from ubiquitous and pervasive computing. These smart objects are expected to generate Big Sensed Data (BSD) that can leverage a great number of new applications. However, this raw BSD needs to be collected efficiently and then processed, analyzed, and possibly stored before becoming high-level information that can be consumed by the applications. So far, data collection mechanisms have focused on localized sensor networks; while the most popular platform for data storage and processing has been the centralized cloud. This tutorial shed light on why these mechanisms are not suitable for current and future requirements of the IoT. In particular, the tutorial discusses large scale data collection mechanisms that are energy efficient and inexpensive, including techniques such as public sensing and crowdsourcing. The data collection techniques considered in the tutorial focus on scalability and quality of service requirements. Furthermore, the tutorial provides in-depth examination of state-of-the-art technologies proposed for software-defined and distributed infrastructures that support the requirements of the IoT. Moreover, the tutorial discusses how BSD can be processed and turned into high-level information that can leverage smart applications. Thus, techniques such as complex-event processing and context-awareness will be reviewed as well, since they are capable of supporting real-time information processing in a distributed infrastructure. We also discuss the challenges of how these technologies and others can be implemented in a distributed architecture to ensure scalability

Tutorial Objectives
Even though many areas related to the IoT have received significant attention from the research community, deploying solutions on a large scale still remains challenging. Research is still largely focused on localized networks, and scalable solutions are scattered. Thus, the idea of a software-defined distributed infrastructure that supports the processing, analysis, networking, and storage requirements of the IoT has recently been introduced as a high potential solution to scalable IoT services. Fortunately, there exists several technologies that can leverage the design of this distributed infrastructure. For example, public sensing and crowdsourcing technologies have been proposed as powerful and inexpensive data collection mechanisms, and have accordingly received attention from the research community [1]. There are also several platforms that now address the heterogeneity challenge in the sensing layer of the IoT [2]. Furthermore, there now exist several technologies leveraging a dynamic and software-defined networking infrastructure. For example, software-defined networking allow the implementation and re-programming of forwarding policies in real-time according to changing networking requirements [3]. In another example, information-centric networking enable content-based communications mainly through the publish/subscribe pattern [4]. These technologies, and others, create a networking infrastructure that can scale with high traffic demands while being able to support dynamic QoS requirements. Another key technology that is quite suitable for IoT infrastructures is fog computing. Here, computing resources are available near the network edge to support processing, network, and storage services, among others. The distributed nature of fog computing means that scalable real-time services can be supported in an IoT infrastructure. One of the techniques that have been recently gaining attention from the research community for processing streams of data in fog computing networks is complex-event processing (CEP) [5], which is capable of transforming raw sensor data into high level information that can leverage intelligent applications. On top of CEP, several reasoning, prediction, and machine learning techniques can be implemented to maximize the utilization of the information.
In this tutorial, the attendees will first learn about the need for an IoT infrastructure and the challenges associated with building one. Attendees will also learn about the advantages of having a software-defined distributed infrastructure for the IoT. They will also get introduced to several key enabling technologies for designing such an infrastructure, with in-depth discussions about their implementation. Attendees will also understand the state-of-the-art in research of all these technologies. Moreover, the tutorial sessions will go into the details of how these technologies can be integrated, and the challenges therein. In the end, attendees of this tutorial will have sufficient knowledge to conduct research into many areas related to software-defined IoT infrastructures, and be able to develop scalable smart services that are suitable for a wide range of applications.

Tutorial Outline

Part I—An overview of the sensing layer of the IoT (40 mins)

1. A quick review of some popular IoT technologies and the latest research efforts into the digitization of everyday objects
2. Heterogeneity of IoT technologies and the interoperability challenges that arise
3. Scalable and energy-efficient data collection- platforms

Part II—The software-defined infrastructure (40 mins)

1. Requirements and challenges of an IoT infrastructure
2. Fog computing architectures for the IoT
3. Complex-event processing (CEP) techniques for developing a distributed IoT infrastructure

Break (20 mins)

Part III—Networking technologies for the infrastructure (40 mins)

1. The dynamic networking quality of service requirements of an IoT infrastructure
2. Software-defined networking (SDN) for the IoT
3. Information-centric networking (ICN) based on publish/subscribe communications
4. The integration of SDN, ICN, and CEP

Part IV—Intelligence techniques for the infrastructure (40 mins)

1. Prediction and reasoning techniques for maximizing information utilization
2. Semantic architectures for interoperability and usability of information

Primary Audience
This tutorial comes at a critical time when global investments in IoT solutions are witnessing a significant boost. Thus, understanding the requirements of an infrastructure that can support these investments is of high importance, and can result in improved efficiency through interoperability solutions and networking of heterogeneous smart objects. The intended audience are researchers and industry persons with interest in the field of IoT, smart cities, fog computing, sensor networks, BSD, or any of the fields addressed in this tutorial.

Novelty
The tutorial will discuss the state-of-the-art in key enabling technologies for IoT infrastructures. Research in these technologies is multi-disciplinary in nature, which often leads to scattered expertise. Thus, one of the important contributions of this tutorial is to offer insight into the integration of many technologies to develop an efficient scalable IoT infrastructure. The presenters have experience in all the topics covered, which will hopefully result in meaningful discussions in many areas.

Biography
Amr El Mougy is currently an assistant professor at the German University in Cairo, Cairo, Egypt. He is the head of the IoT lab and is currently leading several projects such as Networked Appliances, Applications, and Sensing Systems for the Smart City, and iTram: an Information and Communication Technology Framework for Intelligent Transportation Systems, among others. Before that, Amr El Mougy was a post-doctoral fellow at Ottawa University, Ottawa, Canada, where he managed a research project on LTE-based public safety networks. Amr received his PhD from Queen’s University, Kingston, Canada in 2013 and his MSc degree from Concordia University, Montreal, Canada in 2006. He has co-authored several book chapters and has over 30 publications.

Mohamed Ibnkahla is currently a Full Professor and Cisco Industrial Research Chair at the Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada. He was with the Department of Electrical and Computer Engineering, Queen's University, Kingston, Canada (2000-2015), and the Department of Electronics, INP, Toulouse, France (1996-1999). The Cisco Industrial Research Chair is on “Internet of Everything (IoE) Sensor Networks and Technologies”. Dr. Ibnkahla has been leading several projects with industry and government agencies. He is currently involved in a number of projects applying wireless communications in key areas of the e-Society, including: smart power grid, control of renewable energy, water management, public health, environment monitoring, wildlife tracking, food traceability and safety risk monitoring, highway safety, intelligent transportation systems, etc. Mohamed obtained the Ph.D. degree and the Habilitation a Diriger des Recherches degree (HDR) from the National Polytechnic Institute of Toulouse (INP), Toulouse, France, in 1996 and 1998, respectively. He obtained an Engineering degree in Electronics (1992) and a Diplome d'Etudes Approfondies degree (equivalent to MSc) in 1992 all from INP. He has published several books and over 50 peer-reviewed papers.

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T8: Leveraging Big Sensed Data in Vehicular IoT systems

Presented by: Hossam Hassanein & Sharief Oteafy, School of Computing Queen’s University, Kingston, ON, Canada

Time: 14:00–17:30
Room: Fitzgerald

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Abstract—The Internet of Things (IoT) is proliferating on reliable and scalable collection of sensed data. Meanwhile, the growing domain of sensing over smart vehicles and smart devices (tablets, smartphones), are all generating an exponentially increasing amount of data. The ensuing advent of Big Sensed Data (BSD) is generating critical challenges. First, collected data is mainly insightful to each deployed network, any “sense-making” processes to be built upon heterogeneously collected data faces significant interoperability problems, exposing challenges with varying quality, data-labelling inconsistencies, inaccuracies, time-sensitivities and different reporting granularities. Second, sensing systems inherently adopt a collect-and-report model, whereby collected data is indiscriminately pushed onto the networking infrastructure, regardless of the Quality of Information (QoI) or its value (VoI). Not only do we face scalability issues, but establishing reliable Vehicular Information Services on top of BSD is not attainable over inconsistently collected, validated and reported data. Thus, the future of Big Data is hampered by the sheer volume of reported data, its uncalibrated discrepancies, and worse by the flood of redundant and lower quality data. Real-time decision making is inherently built on the efficacy of ubiquitous sensing systems, not on the aggregation of devices that are isolated in operation and management. In a time when important IoT applications such as real-time road monitoring, health Informatics and emergency services require rapid and scalable access to contextual information about patients, mobile crowds and the general public, the status quo falls significantly short.

Tutorial Objectives
We will base our tutorial on three-phases of evolution. First, in Part I we will present a chronological evolution of sensing advancements, and the core challenges that yielded the primitive views on de facto protocols. This will entail discussions on evolution of cooperative sensing protocols designed for IoT. This brief introduction will facilitate an in-depth discussion of why we ended up with current classical trade-offs in public sensing designs, and the disparity in the current status quo. This part will delve into the primitives of the IoT, and how different projects and research directions have hindered its realization.

Part II will cover two components. First, we will detail challenges that are causing current bottlenecks in Vehicular IoT development, especially in terms of scalability, lack of interoperability, and the rise of Big Data and communication-infrastructure ailments. This entails election schemes to reduce and/or aggregate sensor readings, and current efforts to establish Quality of Information (QoI) and Quality of Resource (QoR) metrics to govern the viability of data collected from heterogeneous vehicular sensors. Second, we will cover recent directions in literature (both from academia and industry) in addressing the phases of data accessibility, polling, classification, calibration and pruning. This includes incentive schemes to solicit crowd-based data, and engaging the larger public in contributing real-time data instead of pre-deploying Road Side Units (RSUs) to cover all potential regions/roads of interest. We advocate for severing sense-making processes, especially critical ones with time latency constraints, from pre-deployed architectures. This part of the tutorial will detail the impact of realizing Vehicular sensing systems on-the-fly and the potential proliferation of Information Services based on this paradigm.

In Part III, we will introduce novel paradigms that promise synergistic operation across Vehicular architectures, and the premise of building scalable Information Services. Specifically, we will detail recent efforts in standardizing access to data, provisioning of sensor-oriented services, and the hierarchical naming conventions that will enable access to crowd-solicited/heterogeneous data sources. This encompasses details on standardized formats, formal naming conventions, and the adoption of attribute-based naming systems. In this part we will delve into efforts in leveraging Sensing in the Vehicular Cloud, especially in diverting selective operations and processing on the Edge over Fog Computing architectures. This direction will cover recent directions in multi-tiered Edge offloading, and the integration premise of Cloudlets and end systems with sensing systems. This direction details the potential ubiquity and variable accessibility to sensor networks over the Cloud infrastructure, as a potential parallel to direct accessibility (Via 6LowPAN, BLE and ZigBee). We will also delve into novel models addressing the Smog of Communication caused by the multiplicity of low-power devices in the IoT era, and how we can approach an evolutionary view of IoT based on the aggregated capabilities of its encompassed public sensing systems.

Tutorial Outline

1. Introduction and Evolution of Vehicular IoT
   1. IoT evolution
   2. IoT standards and alliances
   3. Vehicular IoT
2. Challenges of BSD proliferation in Vehicular IoT
3. Break
4. Practical directions for addressing Vehicular Big Data
5. Building Vehicular IoT Information Services over Vehicular Clouds
6. Questions and Discussion

Primary Audience
The scope and depth of discussion will be aimed at researchers and practitioners in Vehicular systems. To achieve this, we touch on particular advances that have been taking place in the standardization, industrial practices and recently published findings. A specific focus will be given to vehicular communication standards such as DSRC, and new mandates for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) operation.

Basic understanding of the operation of the Internet and general protocols in Mobile Ad Hoc networks, will be expected.

Novelty
As researchers investigate novel directions to realize a ubiquitous Vehicular IoT (V-IoT), many underestimate Big Data challenges in massive sensing, lack of cooperation between V-IoT systems, and architectural incompatibilities. This tutorial will survey prominent research endeavours that yield the greatest promise in V-IoT proliferation. We see it prudent to instigate a discussion on the importance of transcending sheer vehicular communication, building novel paradigms for ubiquitous resource synergy, and deriving future systems which capitalize on inherent heterogeneity.

Biography
Hossam S. Hassanein (S’86 - M’90 - SM’06 - F’17) is a leading authority in the areas of broadband, wireless and mobile networks architecture, protocols, control and performance evaluation. His record spans more than 500 publications in journals, conferences and book chapters, in addition to numerous keynotes and plenary talks in flagship venues. Dr. Hassanein has received several recognition and best papers awards at top international conferences. He is the founder and director of the Telecommunications Research (TR) Lab at Queen's University School of Computing, with extensive international academic and industrial collaborations. Dr. Hassanein is a senior member of the IEEE, and is the past chair of the IEEE Communication Society Technical Committee on Ad hoc and Sensor Networks (TC AHSN). He is an IEEE Communications Society Distinguished Speaker (Distinguished Lecturer 2008-2010). Dr. Hassanein is a Fellow of the IEEE and has received several recognitions and best papers awards.

Sharief Oteafy (IEEE S’08–M’13) is an Adjunct Assistant Professor at the School of Computing, Queen’s University. Dr. Oteafy received his PhD in 2013 from Queens University, focusing on adaptive resource management in Next Generation Sensing Networks, introducing the notion of Organic senor networks that adapt to their environment and scale in functionality with resource augmentation. His current research focuses on dynamic architectures for enabling large scale synergy in the Internet of Things; encompassing dynamic resource management across IoT platforms, in addition to managing the proliferation of Big Sensed Data. Dr. Oteafy is actively engaged in the IEEE Communications Society, and an IEEE and ACM member since 2008. He is an active member of the IEEE ComSoc Standards Association and is currently the Ad Hoc and Sensor Networks standards Liaison, and a voting member in the ComSoc Tactile Internet standard WG. Dr. Oteafy co-authored a book on “Dynamic Wireless Sensor Networks”, published by Wiley, and presented over 40 peer-reviewed publications in Sensing systems and the IoT. He co-chaired a number of IEEE workshops, in conjunction with IEEE ICC and IEEE LCN conferences, and served on the TPC of numerous IEEE and ACM symposia. Dr. Oteafy has delivered tutorials on Big Sensed Data management in IEEE ICC, IEEE CAMAD and IEEE Globecom conferences, and serves as an Associate Editor in IEEE Access.

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T9: Onboard Sensor Fusion Methods for Vehicular Platforms by Mohamed Atia, Carleton University, Department of Electronics, Ottawa, ON, Canada. has been cancelled

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T10: Air-to-X Channel Modeling for UAVs, Drones, and Future Air-Ground Communications by David W. Matolak, University of South Carolina has been cancelled

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