T1 Rate-Splitting and Robust Interference Management: Theory and Applications
Sunday, September 9, at 9.00 – 12.30
Room: tbd
ABSTRACT
Numerous techniques have been developed in the last decade for MIMO wireless networks, including among others MU-MIMO, CoMP, Massive MIMO, NOMA, millimetre wave MIMO. All those techniques rely on two extreme interference management strategies, namely fully decode interference and treat interference as noise. Indeed, while NOMA based on superposition coding with successive interference cancellation relies on strong users to fully decode and cancel interference created by weaker users, MU-MIMO/Massive MIMO/CoMP/millimetre wave MIMO based on linear precoding rely on fully treating any residual multi-user interference as noise.
In this tutorial, we depart from those two extremes and introduce the audience to a more general and more powerful transmission framework based on Rate-Splitting (RS) that consists in decoding part of the interference and in treating the remaining part of the interference as noise. This enables RS to softly bridge and therefore reconcile the two extreme strategies of fully decode interference and treat interference as noise.
RS relies on the transmission of common messages decoded by multiple users, and private messages decoded by their corresponding users. As a result, RS pushes multiuser transmission away from conventional unicast-only transmission to non-orthogonal unicast multicast-like transmission and leads to a more general class/framework of strategies. For instance, NOMA and SDMA/MU-MIMO with linear precoding are special cases of RS. RS will be shown to provide significant benefits in terms of spectral efficiencies, reliability and CSI feedback overhead reduction over conventional strategies used/envisioned in LTE-A/5G. The gains of RS will be demonstrated in a wide range of scenarios: multi-user MIMO, massive MIMO, multi-cell MIMO/CoMP, overloaded systems, NOMA, multigroup multicasting, mmwave communications, communications in the presence of RF impairments. Open problems and challenges will also be discussed.
ABOUT THE SPEAKER
Bruno Clerckx is a Reader (Associate Professor) in the Electrical and Electronic Engineering Department at Imperial College London (London, United Kingdom). He received his M.S. and Ph.D. degree in applied science from the Université catholique de Louvain (Louvain-la-Neuve, Belgium) in 2000 and 2005, respectively. From 2006 to 2011, he was with Samsung Electronics (Suwon, South Korea) where he actively contributed to 3GPP LTE/LTE-A and IEEE 802.16m and acted as the rapporteur for the 3GPP Coordinated Multi-Point (CoMP) Study Item. Since 2011, he has been with Imperial College London, first as a Lecturer (2011-2015), then as a Senior Lecturer (2015-2017), and now as a Reader. From March 2014 to March 2016, he also occupied an Associate Professor position at Korea University, Seoul, Korea. He also held visiting research appointments at Stanford University, EURECOM, National University of Singapore and The University of Hong Kong.
He is the author of 2 books, 150 peer-reviewed international research papers, 150 standard contributions and the inventor of 75 issued or pending patents among which 15 have been adopted in the specifications of 4G (3GPP LTE/LTE-A and IEEE 802.16m) standards. Dr. Clerckx served as an editor for IEEE TRANSACTIONS ON COMMUNICATIONS from 2011-2015 and is currently an editor for IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS and IEEE TRANSACTIONS ON SIGNAL PROCESSING. He has been TPC member, symposium chair, TPC chair of many symposia on communication theory, signal processing for communication and wireless communication for several leading international IEEE conferences. He has also been (lead) guest editor for EURASIP Journal on Wireless Communications and Networking, IEEE Access and IEEE Journal on Selected Areas in Communications. He was the editor for 3GPP LTE-Advanced standard technical report on CoMP. He is an Elected Member of the IEEE Signal Processing Society SPCOM Technical Committee. His research area is communication theory and signal processing for wireless networks.
T2 Traffic Aware Interference Management for Flexible 5G Radio Access
Sunday, September 9, at 14.00 – 17.30
Room: tbd
ABSTRACT
Dynamic or flexible time division duplexing (TDD) is an essential 5G ingredient, e.g., in the 3GPP New Radio (NR) specification. This tutorial provides a holistic view for the design of interference management in 5G and beyond networks based on dynamic traffic aware TDD, particularly addressing relevant technology components such as beamformer training, CSI acquisition, resource allocation and interference control. The methods discussed will account for variations in user traffic as well the associated overhead from adapting UL/DL resources. In addition to dynamic TDD, similar cross-link interference scenarios can also appear in integrated access backhaul (IAB) with half-duplex constraint between access links as well as between access and backhaul. Therefore, an unified cross-link interference management needs to be developed that is applicable to both dynamic TDD as well as IAB scenarios. First, an overview of 3GPP NR physical layer aspects is provided. A special focus is given for key technology components enabling dynamic TDD operation in NR. The theoretical performance limits of dynamic TDD systems using scheduling and coordinated beamforming are then briefly explored. Subsequently, low complexity, near optimal distributed solutions that account for the users’ traffic dynamics are considered. Particular emphasis is put on the iterative Forward-Backward (F-B) training based beamformer estimation mechanisms using precoded pilots, as well as, methods to compensate for pilot non-orthogonality and imperfect channel measurements. The feasibility of proposed schemes in the context of 5G radio access will be discussed. The tutorial concludes with some highlights for future research directions.
ABOUT THE SPEAKERS
Antti Tölli (CWC, University of Oulu, FL) (M’08, SM’14) received the Dr.Sc. (Tech.) degree in electrical engineering from the University of Oulu, Oulu, Finland, in 2008. Before joining the Centre for Wireless Communications (CWC) at the University of Oulu, he worked for 5 years with Nokia Networks as a Research Engineer and Project Manager both in Finland and Spain. In May 2014, he was granted a five year (2014-2019) Academy Research Fellow post by the Academy of Finland. Currently, he also holds an Associate Professor position with University of Oulu. During the academic year 2015-2016, he visited at EURECOM, Sophia Antipolis, France, while from August 2018 till June 2019 he is visiting University of California – Santa Barbara, USA. He has authored more than 160 papers in peer-reviewed international journals and conferences and several patents all in the area of signal processing and wireless communications. His research interests include radio resource management and transceiver design for broadband wireless communications with a special emphasis on distributed interference management in heterogeneous wireless networks. He is currently serving as an Associate Editor for IEEE Transactions on Signal Processing. Detailed list of publications is available at http://www.cwc.oulu.fi/~atolli/Publications.pdf.
Juha Karjalainen (S’03, M’10) received his M.Sc.(Tech.) and Dr.Sc degree in electrical engineering from University of Oulu, Finland, in 2001 and 2011. Currently, he is working at Nokia Bell Labs, Finland, as a Senior Specialist. Before he joined the Nokia Bell Labs, he was working with Samsung Electronics as a Principal Standards Engineer. Prior to that, he was working at Renesas Mobile as a Principal Researcher, and with University of Oulu as a Research Scientist and Project Manager as well as Nokia Mobile Phones working as Senior Designer. His research interests include next generation mobile broadband communication systems, multi-antenna transceiver schemes and interference management.
T3 Unlocking new Dimensions in Radio-based Positioning “5G Localization”
Sunday, September 9, at 9.00 – 12.30
Room: tbd
ABSTRACT
5G will be characterized by increased data rates, higher density of devices, and a wide variety of use cases. A technology to satisfy the rate requirements is mmWave, due to the large available bandwidth and directional interference-free transmissions. As a side-effect, mmWave signals are useful for inter-device ranging as well as inter-device angle estimation. In turn, this leads to a potential new positioning technology: 5G localization. This tutorial will cover the basics of the new area 5G localization, covering models; performance bounds; algorithms for localization, tracking, and mapping; and applications. The tutorial presumes basic knowledge on wireless communication and statistical signal processing.
ABOUT THE SPEAKERS
Henk Wymeersch is a Professor in Communication Systems with the Department of Electrical Engineering at Chalmers University of Technology, Sweden. He is also affiliated with the FORCE research center on fiber-optic communication. Prior to joining Chalmers, he was a Postdoctoral Associate during 2006-2009 with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT). Henk Wymeersch obtained the Ph.D. degree in Electrical Engineering/Applied sciences in 2005 from Ghent University, Belgium. For his thesis, he received the 2006 Alcatel Bell Scientific Award. He received a fellowship from the Belgian American Educational Foundation in 2005-2006. He is a member of the IEEE, and served as Associate Editor for IEEE Transactions on Communications (2016-2018), IEEE Transactions on Wireless Communications (2013-present), for IEEE Communication Letters (2009-2013). He served as Guest Editor for IEEE Journal on Selected Areas in Communications (JSAC, special issue on Location-aware Radios and Networks), EURASIP Journal on Wireless Communications and Networking (special issue on Localization in Mobile Wireless and Sensor Networks), and for EURASIP Journal on Advances in Signal Processing (special Issue on Signal Processing Techniques for Anywhere, anytime positioning). In 2015, he served as General Chair of the International Conference on Localization and GNSS.
Gonzalo Seco-Granados received the Ph.D. degree in telecommunications engineering from the Universitat Politècnica de Catalunya, Spain, in 2000. His PhD received the award from Spanish Association of Electrical Engineers. From 2002 to 2005, he was member of the technical staff at European Space Agency, involved in the design of the Galileo System. He did some of the seminal work on the application of antenna arrays in GPS receivers, and he is inventor of patented techniques that are widely used in Galileo receivers. Since 2006, he is an Associate Professor with the Department of Telecommunications and Systems Engineering, Universitat Autonoma de Barcelona, Spain. He has been a principal investigator of more than 30 research projects, and he has co-authored over 230 contributions in journals and international conferences. He is senior member of the IEEE. In 2016, he served as General Co-Chair of the International Conference on Localization and GNSS, and as Executive Co-Chair of the 8th Advanced Satellite Multimedia Systems Conference and the 14th Signal Processing for Space Communications Workshop (ASMS/ SPSC). He is co-organizer of Special Sessions dealing with localization at IEEE CAMSAP 2017 and Asilomar Conference on Signals, Systems, and Computers 2018. In 2014, he was a recipient of the ICREA Academia Award. In 2015, he was a Fulbright Visiting Professor with the University of California at Irvine, CA, USA.
T4 Deep Learning for Communications
Sunday, September 9, at 14.00 – 17.30
Room: tbd
ABSTRACT
In the last decade, deep learning has led to many breakthroughs in various domains, such as computer vision, natural language processing, and speech recognition. Motivated by these successes, researchers all over the world have recently started to investigate applications of this tool to their respective domain of expertise, with communications being one of them. The goal of this tutorial is to provide an introduction to deep learning that will enable the attendees to identify potential applications in their own research field. We give an overview of the very rapidly growing body of literature, explain state-of-the-art neural network architectures and training methods, and go through several promising applications and concepts, such as neural decoding, deep MIMO detection, and autoencoders. The attendees receive tutorial slides and Jupyter notebooks containing code examples which allows them to quickly get up to speed with this new and exciting field. During the break, we demonstrate the world’s first fully neural network-based communications system.
ABOUT THE SPEAKERS
Stephan ten Brink is a faculty member at the University of Stuttgart, Germany, since July 2013, where he is head of the Institute of Telecommunications. From 1995 to 1997 and 2000 to 2003, Dr. ten Brink was with Bell Laboratories in Holmdel, New Jersey, conducting research on multiple antenna systems. From July 2003 to March 2010, he was with Realtek Semiconductor Corp., Irvine, California, as Director of the wireless ASIC department, developing WLAN and UWB single chip MAC/PHY CMOS solutions. In April 2010, he returned to Bell Laboratories as Department Head of the Wireless Physical Layer Research Department in Stuttgart, Germany. Dr. ten Brink is a recipient and co-recipient of several awards, including the Vodafone Innovation award, the IEEE Stephen O. Rice Paper Prize, and the IEEE Communications Society Leonard G. Abraham Prize for contributions to channel coding and signal detection for multiple-antenna systems. He is best known for his work on iterative decoding (EXIT charts) and MIMO communications (soft sphere detection, massive MIMO).
Jakob Hoydis is a member of technical staff at Nokia Bell Labs, France, where he is investigating since several years applications of deep learning for the physical layer. Before this position he was co-founder and CTO of the social network SPRAED and worked for Alcatel-Lucent Bell Labs in Stuttgart, Germany. He received the diploma degree (Dipl.-Ing.) in electrical engineering and information technology from RWTH Aachen University, Germany, and the Ph.D. degree from Supélec, Gif-sur-Yvette, France, in 2008 and 2012, respectively. His research interests are in the areas of machine learning, cloud computing, SDR, large random matrix theory, information theory, signal processing and their applications to wireless communications. He is recipient of the 2012 Publication Prize of the Supélec Foundation, the 2013 VDE ITG Förderpreis, the 2015 Leonard G. Abraham Prize, as well as the Marconi Prize of the IEEE COMSOC. He received the WCNC’2014 best paper award and has been nominated as an Exemplary Reviewer 2012 for the IEEE Communication letters. He has co-authored the textbook Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency in 2017.
Sebastian Cammerer received the B.Sc. and M.Sc. degree (with distinction) in electrical engineering and information technology from University of Stuttgart, Germany, in 2013 and 2015, respectively. During his years of study he worked as a research assistant at multiple institutes of University of Stuttgart. Since 2015 he is a member of research staff at Institute of Telecommunications, University of Stuttgart, and is pursuing his Ph.D. His main research topics are channel coding and machine learning for communications. Further research interests are in the areas of modulation, parallelized computing for signal processing and information theory. He is recipient of the Anton- und Klara Röser Preis 2016, the Rohde&Schwarz Best Bachelor Award 2015 and the VDE-Preis 2016 for his master thesis.
Sebastian Dörner received the B.Sc. and M.Sc. degrees in electrical engineering and information technology in 2014 and 2017, respectively, from the University of Stuttgart, Stuttgart, Germany, where he is currently working toward the Ph.D. degree. He is recipient of the Dr. Gunter Woysch Award 2017 for his master thesis. During his years of study, he was a Research Assistant with multiple institutes of the University of Stuttgart and as a GLT Operator with Hawk-Eye Innovations, Sony Europe. Since April 2017, he has been a member of research staff with the Institute of Telecommunications, University of Stuttgart. His main research topic is applying machine learning techniques to different areas of communication systems. Further research interests include machine learning in general, parallelized GPU computing, channel coding, SDR and signal processing with machine learning tools.
T5 Towards Real-Time Wireless Control via Ultra-Reliable and Low-Latency Communications
Sunday, September 9, at 9.00 – 12.30
Room: tbd
ABSTRACT
Recently, wireless networks are undergoing a transition from connecting people to connecting things, which will allow human interaction with the physical world in a real-time fashion, e.g., tactile internet, industrial automation, self-driving vehicles, and remote surgery. Therefore, future wireless networks need to support real-time control with Ultra-Reliable and Low-Latency Communications (URLLC), which is also one of the major goals in fifth generation (5G) communication systems. In this tutorial, we discuss some fundamental design aspects and challenges to enable the real-time control in future wireless networks. In particular, we introduce the recent advances in communication-control co-design to capture the strong dynamics and interdependencies between wireless communication and control systems. We also discuss the co-design of Physical (PHY) and Medium Access Control (MAC) layers to guarantee URLLC requirements under limited wireless resource. Finally, we will discuss open problems and potential research directions in URLLC.
ABOUT THE SPEAKERS
Guodong Zhao (SM’16) received his Ph.D. Degree from Beihang University, Beijing, China, in 2011 and his B.E. degree from Xidian University, Xi’an, China, in 2005. He visited the Hong Kong University of Science and Technology, Hong Kong, in 2012.5-2013.8, Lehigh University, USA, in 2016.7-2017.1, and University of Glasgow, UK, in 2017.10-2017.11. He is now an associate professor at University of Electronic Science and Technology of China (UESTC) and an honorary lecturer at University of Glasgow. His current research interests are within the areas of wireless communications and control. He published over 50+ papers in IEEE journals and conferences. In 2012, he received the best paper award from IEEE Global Telecommunication Conference (Globecom) and the best Ph.D. thesis award from Beihang University.
Changyang She (M’17) received his B. Eng and Ph.D. degrees in Electronics and Information Engineering from Beihang University, Beijing, China in 2012 and 2017, respectively. He was a postdoctoral research fellow with Singapore University of Technology and Design. He is now a postdoctoral research Associate with the University of Sydney. His research interests lie in the areas of ultra-reliable and low-latency communications, machine type communication, big data for resource allocation in wireless networks and energy efficient transmission in 5G systems. He has given a tutorial on ultra-reliable and low-latency communications in IEEE International Conference on Communications in China (ICCC) 2017.
Muhammad Ali Imran (M’03, SM’12) received his M.Sc. (Distinction) and Ph.D. degrees from Imperial College London, UK, in 2002 and 2007, respectively. He is a Professor in Communication Systems in University of Glasgow, Vice Dean of Glasgow College UESTC. He is the Head of Communications, Sensing and Imaging research group and leads the 5G research activities in Glasgow. He has led a number of multimillion-funded international research projects encompassing the areas of energy efficiency, fundamental performance limits, sensor networks and self-organising cellular networks. He has supervised 30+ successful PhD graduates and published over 300 peer-reviewed research papers including more than 20 IEEE Transaction papers. He has been awarded IEEE Comsoc’s Fred Ellersick award 2014, FEPS Learning and Teaching award 2014, Sentinel of Science Award 2016, and twice nominated for Tony Jean’s Inspirational Teaching award.
T6 End-to-end Network Slicing and Orchestration for Industry Verticals
Sunday, September 9, at 14.00 – 17.30
Room: tbd
ABSTRACT
The massive deployment of smart devices, broadband and mission critical services are paving the way for a novel and disruptive communication network design that will enable massive capacity, quasi-zero delay, faster service development, flexibility, elasticity and optimal deployment, less energy consumption, enhanced security, privacy by design, and connectivity to billions of devices with less predictable traffic patterns.
To meet such challenges, large consortia promote solutions for the softwarization of networks and virtualization of federated cloud environments by means of the novel network slicing concept. This is further supported by the application verticals evolution with specific and contradicting demand characteristics: i) the Media vertical segment fostering the transition from the traditional linear broadcasting services to OTT (Over The Top) streaming services, ii) the Energy vertical segment shifting from a closed, monolithic and highly predictable infrastructure to an open, multi-owned and multi-tenancy, decentralized ecosystem and iii) the Smart City vertical tackling the key attributes of 5G networks including higher speeds for media/VR applications, more adaptive response times to support time-sensitive applications, such as vehicle-to-vehicle communications. This emerging ecosystem built for a vertical-oriented design of next-generation networks (5G and beyond) is little understood in academia and industry, and there is a fundamental lack of approaches for modeling and optimizing it with focus on the diverse requirements coming from different vertical markets.
This tutorial aims at filling this gap, providing in detail the enabling techniques to allow multiple vertical-oriented services to coexist by sharing the same physical infrastructure and, in turn, re-thinking the overall business model for next-generation networks. In particular, it will shed the light on the main technical challenges and expected solutions for realizing a fully-fledged end-to-end orchestration while striking up discussion on required implementations within realistic frameworks by means of basic machine-learning techniques. A new approach for modeling and optimizing the radio access networks of cellular networks with network slicing will be illustrated and some results will be presented.
ABOUT THE SPEAKERS
Vincenzo Sciancalepore is a 5G Researcher and RAN specialist at NEC Europe Ltd., Germany. He is currently focusing his activity in the area of network virtualization and network slicing challenges with an extended vision on mobile edge computing research topic.
He has been involved in a number of European Projects and several published international Research Papers as well as Patents. He is currently involved in the IEEE Emerging Technologies Committee leading the initiatives on Software Defined Networking & Network Function Virtualization.
He is also member of IEEE ComSoc (S’11-M’15). He received his M.Sc. degree in Telecommunications Engineering and Telematics Engineering in 2011 and 2012, respectively, whereas in 2015, he received a double Ph.D. degree from Politecnico di Milano and Universidad Carlos III de Madrid. From 2011 to 2015 he was Research Assistant at IMDEA Networks, focusing on inter-cell coordinated scheduling for LTE Advanced networks and device-to-device communication. He was also the recipient of the national award for the best Ph.D. thesis in the area of communication technologies (Wireless and Networking) issued by GTTI in 2015.
Marco di Renzo was born in L’Aquila, Italy, in 1978. He received the Laurea (cum laude) and Ph.D. degrees in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the Habilitation à Diriger des Recherches (Doctor of Science) degree from University Paris-Sud, France, in 2013. Since 2010, he has been a Chargé de Recherche CNRS (CNRS Associate Professor) in the Laboratory of Signals and Systems (L2S) of Paris-Saclay University – CNRS, CentraleSupélec, Univ Paris Sud, Paris, France. He serves as the Associate Editor-in-Chief of IEEE Communications Letters, and as an Editor of IEEE Transactions on Communications, and IEEE Transactions on Wireless Communications. He is a Distinguished Lecturer of the IEEE Vehicular Technology Society and IEEE Communications Society, and a Senior Member of the IEEE. He is a recipient of several awards, including the 2013 IEEE-COMSOC Best Young Researcher Award for Europe, Middle East and Africa, the 2013 NoE-NEWCOM# Best Paper Award, the 2014-2015 Royal Academy of Engineering Distinguished Visiting Fellowship, the 2015 IEEE Jack Neubauer Memorial Best System Paper Award, the 2015-2018 CNRS Award for Excellence in Research and Ph.D. Supervision, the 2016 MSCA Global Fellowship (declined), the 2017 SEE-IEEE Alain Glavieux Award, the 2018 IEEE ICNC Silver Contribution Award, and 6 Best Paper Awards at IEEE conferences (2012 and 2014 IEEE CAMAD, 2013 IEEE VTC-Fall, 2014 IEEE ATC, 2015 IEEE ComManTel, 2017 IEEE SigTelCom).
T7 Wireless Communications and Networking with Unmanned Aerial Vehicles
Sunday, September 9, at 9.00 – 12.30
Room: tbd
ABSTRACT
Unmanned aerial vehicles (UAVs) are expected to become an integral component of future smart cities. In fact, UAVs are expected to be widely and massively deployed for a variety of critical applications that include surveillance, package delivery, disaster and recovery, remote sensing, and transportation, among others. More recently, new possibilities for commercial applications and public service for UAVs have begun to emerge, with the potential to dramatically change the way in which we lead our daily lives. For instance, in 2013, Amazon announced a research and development initiative focused on its next-generation Prime Air delivery service. The goal of this service is to deliver packages into customers’ hands in 30 minutes or less using small UAVs, each with a payload of several pounds. 2014 has been a pivotal year that has witnessed an unprecedented proliferation of personal drones, such as the Phantom and Inspire from DJI, the Lone Project from Google, AR Drone and Bebop Drone from Parrot, and IRIS Drone from 3D Robotic. Such a widespread deployment of UAVs will require fundamental new tools and techniques to analyze the possibilities of wireless communications using UAVs and among UAVs.
In the telecom arena, flying drones are already envisioned by operators to help provide broadband access to under-developed areas or provide hot-spot coverage during sporting events. More generally flying drones are expected to become widespread in the foreseeable future. These flying robots will develop a unique capability of providing a rapidly deployable, highly flexible, wireless relaying architecture that can strongly complement small cell base stations. UAVs can provide “on-demand” densification, help push content closer to the end-user at a reduced cost and be made autonomous to a large extent: Airborne relays can self-optimize positioning based on safety constraints, learning of propagation characteristics (including maximizing line of sight probability) and of ground user traffic demands. Finally, UAVs can act as local storing units making smart decisions about content caching. Thus airborne relays offer a promising solution for ultra-flexible wireless deployment, without the prohibitive costs related to fiber backhaul upgrading. Yet another example is when UAVs can be used as flying base stations that can be used to serve hotspots and highly congested events, or to provide critical communications for areas in which no terrestrial infrastructure exists (e.g., in public safety scenarios or in rural areas). Clearly, UAVs will revolutionize the wireless industry and there is an ever increasing need to understand the potential and challenges of wireless communications using UAVs.
To this end, this tutorial will seek to provide a comprehensive introduction to wireless communications using UAVs while delineating the potential opportunities, roadblocks, and challenges facing the widespread deployment of UAVs for communication purposes. First, the tutorial will shed light on the intrinsic properties of the air-to-ground and air-to-air channel models while pinpointing how such channels differ from classical wireless terrestrial channels. Second, we will introduce the fundamental performance metrics and limitations of UAV-based communications. In particular, using tools from communication theory and stochastic geometry, we will provide insights on the quality-of-service that can be provided by UAV-based wireless communications, in the presence of various types of ground and terrestrial networks. Then, we will analyze and study the performance of UAV-to-UAV communications. Subsequently, having laid the fundamental performance metrics, we will introduce the analytical and theoretical tools needed to understand how to optimally deploy and operate UAVs for communication purposes. In particular, we will study several specific UAV deployment and mobility scenarios and we will provide new mathematical techniques, from optimization, game, and probability theory that can enable one to dynamically deploy and move UAVs for optimizing wireless communications. Moreover, we will study, in detail, the challenges of resource allocation in networks that rely on UAV-based communications. Throughout this tutorial, we will highlight the various performance tradeoffs pertaining to UAV communications ranging from energy efficiency to mobility and coverage. The tutorial concludes by overviewing future opportunities and challenges in this area.
ABOUT THE SPEAKERS
Walid Saad (S’07, M’10, SM’15) received his Ph.D degree from the University of Oslo in 2010. Currently, he is an Associate Professor at the Department of Electrical and Computer Engineering at Virginia Tech, where he leads the Network Science, Wireless, and Security (NetSciWiS) laboratory, within the Wireless@VT research group. His research interests include wireless networks, machine learning, game theory, cybersecurity, unmanned aerial vehicles, and cyber-physical systems. Dr. Saad is the recipient of the NSF CAREER award in 2013, the AFOSR summer faculty fellowship in 2014, and the Young Investigator Award from the Office of Naval Research (ONR) in 2015. He was the author/co-author of six conference best paper awards at WiOpt in 2009, ICIMP in 2010, IEEE WCNC in 2012, IEEE PIMRC in 2015, IEEE SmartGridComm in 2015, and EuCNC in 2017. He is the recipient of the 2015 Fred W. Ellersick Prize from the IEEE Communications Society and of the 2017 IEEE ComSoc Best Young Professional in Academia award. From 2015-2017, Dr. Saad was named the Stephen O. Lane Junior Faculty Fellow at Virginia Tech and, in 2017, he was named College of Engineering Faculty Fellow. He currently serves as an editor for the IEEE Transactions on Wireless Communications, IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, and IEEE Transactions on Information Forensics and Security.
Mehdi Bennis (S’07, AM’08, SM’15) received his M.Sc. degree in electrical engineering jointly from EPFL, Switzerland, and the Eurecom Institute, France, in 2002. He obtained his Ph.D. from the University of Oulu in December 2009 on spectrum sharing for future mobile cellular systems. Currently he is an associate professor at the University of Oulu and an Academy of Finland research fellow. His main research interests are in radio resource management, heterogeneous networks, game theory, and machine learning in 5G networks and beyond. He has co-authored one book and published more than 100 research papers in international conferences, journals, and book chapters. He was the recipient of the prestigious 2015 Fred W. Ellersick Prize from the IEEE Communications Society, the 2016 Best Tutorial Prize from the IEEE Communications Society, and the 2017 EURASIP Best Paper Award for the Journal of Wireless Communications and Networks.