Abstract—The limitations of MIMOs relying on co-located array-elements are highlighted and it is shown, how the single-antenna aided cooperative mobiles may circumvent these limitations by forming MIMOs having distributed elements. This concept is also referred to a Virtual Antenna Arrays (VAA). Then the corresponding amplify-forward and decode-forward protocols as well as their hybrids are studied. Channel coding has to be specifically designed for the VAAs in order to prevent avalanche-like error-propagation. Hence sophisticated three-stage-concatenated iterative channel coding schemes are proposed and it is argued that in the absence of accurate channel information at the relays the best way forward might be to use multiple-symbol differential detection.
Indeed, it is rather unrealistic to expect that an altruistically relaying handset would also accurately estimate the source-relay channel for the sake of high-integrity coherent detection. EXIT-chart-aided designs are used for creating near-capacity solutions and a range of future research directions as well as open problems are stated.
Tutorial Objectives In the early days of wireless communications the research community used to view multipath-induced dispersion as an undesirable propagation phenomenon, which could only be combatted with the aid of complex channel equalizers. The longer the Channel Impulse Response (CIR) was, the more complex the channel equalizer became. However, provided that the complexity of a sufficiently high-memory channel equalizer was affordable, the receiver could benefit from the fact that the individual propagation paths faded independently. To leaborate a little further, even if one of the paths was experiencing a high attenuation, there was a good chance that some of the other paths were not, which led to a potential diversity gain.
However, if the channel does not exhibit several independently fading paths, techniques of artificially inducing diversity may have to be sought. A simple option is to employ a higher direct-sequence spreading factor, which results in a higher number of resolvable multipath components and hence in an increased diversity gain. Naturally, this is only possible if either the available bandwidth may be extended according to the spreading factor or the achievable bitrate is reduced by the same factor. A whole host of classic diversity combining techniques may be invoked then for recovering the original signal.
An alternative technique of providing multiple independently faded replicas of the transmitted signal is to employ relaying, distributed space-time coding or some other cooperation-aided procedure, which is the subject of this course. One could also view the benefits of decode-and-forward based relaying as receiving and then flawlessly regenerating and retransmitting the original transmitted signal from a relay - provided of course that the relay succeeded in error-freely detecting the original transmitted signal.
This course reviews the current state-of-the-art and proposes a number of novel relaying and cooperation techniques. An important related issue is the availability or the absence accurate channel information, which leads to the concept of coherent versus non-coherent detection at the realys and at the destination. Similarly, the related initial synchronization issues also have to be considered.
Naturally, when using hard-decisions in the transmission chain, we discard valuable soft-information, which results in an eroded performance, albeit also reduces the complexity imposed. Hence the hard- versus soft-decoding performance trade-off will also be explored in the course, along with the benefits of interleaved random space-time coding invoked for multi-source cooperation.
Another important aspect of cooperative communications is constituted by the so-called Cooperative Multi-Point Processing (COMP) technique, which jointly processes all the signals gleaned at all the base-stations (BSs), which will also be covered by the proposed course. In most existing studies he interconnection of all the BSs is assumed to be perfect. By contrast, in this course realistic dispersion-contaminated optical interconnections will be considered.
An Irregular Distributed Space-Time (Ir-DST) coding scheme is studied in the context of a twin-relay aided network in which the successive relaying protocol is employed. A tight upper-bound of the successive relaying aided network’s capacity is given. The distributed codes at the source and relays are jointly designed with the aid of EXtrinsic Information Transfer (EXIT) charts for the sake of high-integrity operation at Signal-to-Noise Ratios (SNRs) close to the corresponding network’s capacity. Finally, it is shown that our proposed Ir-DST coding scheme is capable of near-capacity cooperative communications in the successive relaying aided network, which is an explicit benefit of our joint source-and-relay mode design.
Distributed Self-Concatenated Codes for Low-Complexity Power-Efficient Cooperative Communication
We study a Distributed Binary Self-Concatenated Coding scheme using Iterative Decoding (DSECCC-ID) for cooperative communications. The DSECCC-ID scheme is designed with the aid of binary Extrinsic Information Transfer (EXIT) charts. The source node transmits SECCC symbols to both the relay and the destination nodes during the first transmission period. The relay performs SECCC-ID decoding. It then re-encodes the information bits using a Recursive Systematic Convolutional (RSC) code during the second transmission period. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel-concatenated SECCC-ID encoder. At the destination node, three-component DSECCC-ID decoding is performed. It is shown that the performance of the DSECCCID exactly matches the EXIT chart analysis. The EXIT chart gives us an insight into operation of the distributed coding scheme which enables us to significantly reduce the transmit power of the system.
Resource-Optimized Differentially Modulated Hybrid AF/DF Cooperation Dispensing with Channel Estimation
In multi-user cellular uplinks cooperating mobiles may share their antennas in order to achieve transmit diversity by forming a virtual antenna array (VAA) in a distributed fashion. In this paper, based on the minimum BER criterion, we investigate cooperating-user-selection (CUS) and adaptive-power-allocation (APA) for two types of differentially modulated cooperative cellular uplinks requiring no channel state information (CSI) at the receiver, namely, for the differential-amplify-and-forward (DAF) and the selective differential-decode-and-forward (DDF) assisted systems. They both employ multiple symbol differential sphere detection (MSDSD) to combat rapid-fading-induced performance degradation. More specifically, we investigate the cooperative-protocol-selection (CPS) of the uplink system in conjunction with a beneficial CUS as well as the APA scheme in order to further improve the achievable end-to-end performance, leading to a resource-optimized hybrid AF/DF cooperative system. Hence, a number of cooperating MSs may be adaptively selected from the available MS candidate pool and the cooperative protocol employed by a specific cooperating MS may also be adaptively selected in the interest of achieving the best possible BER performance.
Physical-layer Algebraic Network Coding and Superposition Coding for the Multi-Source Cooperation Aided Uplink
In this paper, we consider coding schemes designed for energy efficient multi-source cooperation. More explicitly, we propose both a powerful superposition coding scheme and a physical-layer algebraic network coding scheme. The concept of generalised network coding is introduced and the relation between superposition coding and network coding is revealed. Our simulation results demonstrate that both of the proposed schemes are capable of performing close to the outage probability bound at the lower end of the target transmit power range. Moreover, compared to the superposition coding scheme considered, the proposed algebraic network coding arrangement imposes a lower complexity at the cost of a slight performance degradation, while maintaining the same throughput and delay.
Cooperative Differential Space-Time Spreading for the Asynchronous Relay Aided CDMA Uplink Using Interference Rejection Spreading Code
A differential Space-Time Coding (STC) scheme designed for asynchronous cooperative networks, where neither channel estimation nor symbol-level synchronization is required at the cooperating nodes. More specifically, our system employs differential encoding during the broadcast phase and a Space-Time Spreading (STS)-based amplify-and-forward scheme during the cooperative phase in conjunction with interference rejection direct sequence spreading codes, namely Loosely Synchronized (LS) codes. Our simulation results demonstrate that the proposed Cooperative Differential STS (CDSTS) scheme is capable of combating the effects of asynchronous uplink transmissions without any channel state information, provided that the maximum synchronization delay of the relay nodes is within the width of IFW. It will be demonstrated that in the frequency-selective environment considered our CDSTS arrangement is capable of exploiting both space-time diversity and multi-path diversity with the aid of a RAKE combiner.
Cooperative Downlink Multicell Pre-processing Relying on Reduced-Rate Back-haul Data Exchange
Different-complexity Multi-Cell Pre-processing (MCP) schemes employing Distributed Signal-to-Interference Leakage plus-Noise-Ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison to the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the throughput achievable in the cell-edge area and offering different geographic rate profile distributions as well as meeting different delay requirements.
Imperfect Digital Fibre Optic Link Based Cooperative Distributed Antennas with Fractional Frequency Reuse in Multicell Multiuser Networks
The achievable throughput of the entire cellular area is investigated, when employing fractional frequency reuse techniques in conjunction with realistically modelled imperfect optical fibre aided distributed antenna systems (DAS) operating in a multicell multiuser scenario. Given a fixed total transmit power, a substantial improvement of the cell-edge area’s throughput can be achieved without reducing the cell-centre’s throughput. The cell-edge’s throughput supported in the worst-case direction is significantly enhanced by the cooperative linear transmit processing technique advocated. Explicitly, a cell-edge throughput of eta = 5 bits/s/Hz may be maintained for an imperfect optical fibre model, regardless of the specific geographic distribution of the users.
Primary Audience Whilst this overview is ambitious in terms of providing a research-oriented outlook, potential attendees require only a modest background in wireless networking and communications. The mathematical contents are kept to a minimum and a conceptual approach if adopted. Postgraduate students, researchers and signal processing practitioners as well as managers looking for cross-pollination of their experience with other topics may find the coverage of the presentation beneficial. The participants will receive the set of slides as supporting material and they may find the detailed mathematical analysis in the above-mentioned books.
Novelty In contrast to other cooperative communications research overviews:
1. Both semi-analytical results relying on EXIT charts as well as Monte-Carlo simulation based results are provided and confirm each other;
2. All concepts are built up from basics, requiring a modest prior knowledge;
3. Radically new near-capacity channel-coded solutions are designed;
4. Generic design guidelines are provided;
Biography Lajos Hanzo (http://www-mobile.ecs.soton.ac.uk) Royal Society Wolfson Fellow, FREng, FIEEE, FIET, Fellow of EURASIP, DSc received his degree in electronics in 1976 and his doctorate in 1983. In 2009 he was awarded the honorary doctorate Doctor Honaris Causa by the Technical University of Budapest. During his 35-year career in telecommunications he has held various research and academic posts in Hungary, Germany and the UK. Since 1986 he has been with the School of Electronics and Computer Science, University of Southampton, UK, where he holds the chair in telecommunications. He has successfully supervised 80 PhD students, co-authored 20 John Wiley/IEEE Press books on mobile radio communications totalling in excess of 10 000 pages, published 1400+ research entries at IEEE Xplore, acted both as TPC and General Chair of IEEE conferences, presented keynote lectures and has been awarded a number of distinctions. Currently he is directing an academic research team, working on a range of research projects in the field of wireless multimedia communications sponsored by industry, the Engineering and Physical Sciences Research Council (EPSRC) UK, the European IST Programme and the Mobile Virtual Centre of Excellence (VCE), UK. He is an enthusiastic supporter of industrial and academic liaison and he offers a range of industrial courses. He is also a Governor of the IEEE VTS. During 2008 - 2012 he was the Editor-in-Chief of the IEEE Press and since 2009 he has been a Chaired Professor also at Tsinghua University, Beijing. For further information on research in progress and associated publications please refer to http://www-mobile.ecs.soton.ac.uk
Abstract—Next generation communication systems are often envisaged as an interconnected set of a variety of autonomous communication entities each with a particular set of quality-of-service requirements competing for acquiring access to limited shared resources. Next generation heterogeneous networks act as a vital technical enabler for future internet-of-things. Multi-Objective Optimization (MO) provides a capable analytical tool for modelling and investigating the behaviours of heterogeneous communication networks and offers critical information for designing efficient interoperations among autonomous entities.
This tutorial briefly covers the analytical foundation of convex and non-convex MO including, the concept of optimality and non-dominance, stability and robustness as well interactive and evolutionary techniques for obtaining optimal solutions. A variety of MO applications are then discussed including instructor's recent research works in spectrum sharing, adaptive cognitive beam-forming and inter-system bargaining protocol design for cognitive cellular networks.
Tutorial Objectives Motivated by superb analytical tools provided by MO for modelling sophisticated heterogeneous communication networks with shared radio and network resources, the main objective of this tutorial is to present an overview on the analytical foundation of the MO. We then provide the audiences with instances of MO applications in modelling, design and performance evaluation of sophisticated communication systems. The tutorial then highlights the potentials of MO in providing technical insights required for designing the next generation wireless communication systems along with its pros-and-cons comparing to other tools such as game theory.
Part I: Theoretical Foundations
Optimization with multiple objectives
MO modelling and notion of optimality
Classification of MO problems
Efficiency and non-dominance
Weighted sum methods and scalarization techniques
Multi objective linear programming
MO NP-Hard problems
Sequential and evolutionary methods for finding the solutions
Part II: Applications
Ad-hoc routing design
Theoretical bounds on achievable capacity in spectrum sharing systems
Design and performance evaluation of cognitive cellular systems
Adaptive cognitive beam-forming design
Inter-system bargaining protocol design for coexisting cognitive cellular networks
Primary Audience This tutorial is suitable for graduate students and researchers in the area of wireless communication networks. In particular the subject area is of interest to those who are involved with research and development activities in designing radio resource allocation schemes and spectrum access strategies for the next generation communication networks. This tutorial is also ideal for researchers who would like to expand their set of analysis techniques and/or who would like to use MO in their research.
Novelty There is a huge interest in the wireless communication research community for adopting new analytical frameworks fit for designing and performance evaluation of the next generation wireless communication systems. MO provides a set of great analytical tools thus significantly facilities such design.
Biography Keivan Navaie (SMIEEE) received his Ph.D. in 2004. From March to November 2004, he was with the School of Mathematics and Statistics, Carleton University, Ottawa, Canada, as a Postdoctoral Research Fellow working on stochastic modelling of wireless networks. From December 2004 to September 2006, he was with the Broadband Communication and Wireless System (BCWS) Centre, Carleton University, Ottawa, Canada where he was the project manager of BCWS participation in European Union 6th Framework integrated project, the Wireless World Initiative New Radio (WINNER) on beyond 3G wireless systems. From September 2006 to July 2011 he was with the Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran. From July 2011 to November 2014 he has been with the School of Electrical and Computer Engineering, University of Leeds, Leeds, UK. He is currently a Senior Lecturer in the school of Computing and Communications, University of Lancaster, Lancaster, UK also a visiting research scientist in Telefonica Research and Innovation, Barcelona, Spain. His research interests lie in the field of radio resource allocation for wireless communication systems, dynamic spectrum allocation, cognitive radio networks, cooperative communications and stochastic network modeling. He has published more than 100 papers in peer reviewed journal and conference proceedings. Dr. Navaie is on the editorial board of the European Transactions on Telecommunications. He has also served as (co)Chair of Wireless Network Track, IEEE VTC2012-Spring in Yokohama, Japan and IEEE 8th International Workshop on Wireless Network Measurements WiNMee 2012 in Paderborn, Germany, IEEE VTC2014-Spring in Seoul, South Korea, and IEEE WCNC 2014 in Istanbul, Turkey. He is the recipient of the 2011 IEEE Iran Section Young Investigator award. His paper, “Access strategies for spectrum sharing in fading environment: Overlay, underlay and mixed,” was in the IEEE Communication Society Best readings on Cognitive Radio 2012. Dr. Navaie is Senior Member of the IEEE, and a Chartered Engineer in the UK.
Abstract—This tutorial comprehensively explores visible light communication (VLC). It explains how VLC has evolved during the 15 years from a relatively low data-rate point-to-point wireless communication system to a gigabit wireless networking technology, which we refer to as Li-Fi. The tutorial demonstrates how Li-Fi enables full cellular networking including multiuser access, full duplex communication and handover. We will work out the fundamental differences to radio frequency (RF) communications, and discuss opportunities and limitations. In this context, the tutorial will address general misconceptions such as: â€œthis is a line-of-sight technologyâ€, â€œit does not work in sun lightâ€, â€œthe lights cannot be dimmedâ€, â€œthere are no Li-Fi products on the marketâ€, etc. We will discuss state-of-the-art physical layer and networking techniques that are specifically developed for Li-Fi. This includes techniques to realise effective modulation, diversity, cooperative transmission, MIMO, multiuser access and interference mitigation by taking into account the specific features of VLC. We will discuss the opportunities Li-Fi will generate to realise hybrid Li-Fi/RF systems for effective load balancing and new sleep mode concepts for significantly improved overall energy efficiency. The tutorial also reviews novel devices such as micro LEDs, single photons avalanche diodes (SPAD) which have the potential to significantly enhance future Li-Fi systems. We will provide latest results from application studies. The tutorial closes with a demonstration of Li-Fi.
Tutorial Objectives PHYSICAL LAYER (1.5h)
To understand the key physical layer differences between RF and Li-Fi, and their impact on the design of techniques for Li-Fi such as modulation, MIMO, cooperative multipoint transmission, interference mitigation and diversity
To understand the capacity limits of an intensity modulation / direct detection transmission link from a theoretical and a practical perspective
To understand the propagation channel and how it impacts practical physical layer designs
To get an overview of state-of-the-art optical components and how they can be used to enhance link margins
To get guidelines how to design massive MIMO Li-Fi systems and to understand the physical limitations
To understand how modulation and dimming can be achieved at the same time
To understand how latest record speeds of 4 Gbps from a single LED, and 15 Gbps from mixed color LEDs have been achieved
VLC NETWORKING (1.5h)
To understand how multiuser access can be achieved effectively
To appreciate the opportunities that optical device characteristics offer such as field of view (FoV) of LEDs and photodiodes for the design of interference mitigation and diversity techniques.
To obtain an overview of published work on load balancing techniques for hybrid Li-Fi / RF systems assuming user mobility and understand open issues
To receive an overview of existing interference mitigation techniques in Li-Fi networks and understand open issues
To receive a summary on studies on the capacity per unit area when assuming existing lighting infrastructures as Li-Fi networks, or attocellular networks
To understand optimisation constraints in attocellular networks which serve a dual purpose of illumination and high speed wireless communications.
To see a Li-Fi system in action
Brief historical notes
The optical channel
Data modulation principles applicable to incoherent light sources
Intensity modulation / direct detection (IM/DD)
Pulsed modulation techniques
Modified OFDM for IM/DD
Optical MIMO techniques
Diffuse MIMO systems
Line-of-sight MIMO systems
Interference characterisation and mitigation in Li-Fi networks
Interference mitigation techniques
Cooperative multipoint (CoMP) techniques
Multiuser access in Li-Fi networks
Load balancing in hybrid Li-Fi / RF networks
Li-Fi application studies and reported results
Performance improvements of RF wireless indoor networks augmented by an optical attocell layer
Primary Audience This tutorial is for MSc and PhD students as well as postdoctoral fellows interested in optical wireless communications. It should also be of inerest for patent examiners as this is a rapidly emerging field.
Novelty To the best of my knowledge there has not been a tutorial on VLC which considers VLC as a full wireless networking technology â€“ this is what we refer to as Li-Fi. Consequently, it covers multiuser access, interference mitigation and hybrid RF / VLC systems, to name only a few unique features of this tutorial.
Biography Harald Haas holds the Chair of Mobile Communications at the University of Edinburgh. His main research interests are in visible light communications, hybrid optical wireless and RF communications, and interference coordination in wireless networks. Professor Haas has first introduced and pioneered Spatial Modulation. He introduced and coined â€˜Li-Fiâ€™ which was listed among the 50 best inventions in TIME Magazine 2011. He was an invited speaker at TED Global 2011, and his talk has been watched online more than 1.5 million times. He is co-founder and chief scientific officer (CSO) of pureLiFi Ltd. Professor Haas holds 29 patents and has more than 25 pending patent applications. He has published 300 conference and journal papers including a paper in Science. He was a recipient of the prestigious Established Career Fellowship from the EPSRC (Engineering and Physical Sciences Research Council) in 2012. Haas is recipient of the Tam Dalyell Prize 2013 awarded by the University of Edinburgh for excellence in engaging the public with science. In 2014 Prof. Haas was selected as one of 10 EPSRC RISE Leaders in the UK recognising inspirational scientists and engineers.
Abstract—This tutorial aims to furnish the audience with the essential tools to understand the fundamentals of electric vehicles, their interaction with the smart grid and introduce the state-of-the-art architectures, models and networks for the electric vehicle infrastructure. Utilities, telecom operators, OEMs, service providers and researchers are among the target audience.
Tutorial Objectives Electric vehicles pose a number of challenges to the smart grid due to their heavy charging load while vehicle batteries emerge as promising Distributed Energy Resources (DERs) that can be used for the benefit of the smart grid. Challenges and opportunities emerging from electric vehicle integration to the smart grid brought forward numerous recent works that address architectures, models and networks to enable communications and control for electric vehicles. Electric vehicle and smart grid interaction is a newly flourishing research field receiving significant attention from communications, power and automotive societies.
This tutorial aims to furnish the audience with the essential tools to understand the fundamentals of electric vehicles and their interaction with the smart grid, introduce the state-of-the-art architectures, models and networks for electric vehicle infrastructure and provide a comprehensive list of open issues. Utility operators, telecom operators, electric vehicle OEMs, electric vehicle service providers, university professors, researchers and students are among the target audience. The tutorial will start with fundamental definition of the electric vehicles and the smart grid concepts and gradually move on to more advanced topics including queuing models, network calculus, optimization models and communication networks. Non-expert audience will be smoothly guided to advanced topics while a balance will be maintained for expert users who already have a basic understanding of smart grid and willing to master the recent advances and learn the open issues in the subject matter.
Introduction to Electric Vehicles and the Smart Grid
Electric vehicle batteries
Electric vehicle supply equipment types
Fundamentals of generation, transmission and distribution in the smart grid
Challenges and Opportunities Emerging from Electric Vehicles and Smart Grid Interaction
--Uncontrolled charging and its impacts on peak load
--Distribution system overloading (impacts on transformers, feeders, etc.)
--Electric vehicles as Distributed Energy Resources (DER) for microgrids
--Electric vehicles for regulation
Communication Technologies and Networks for the Electric Vehicle Infrastructure
Wireless communication technologies (Zigbee, WiFi, WIMAX, LTE, etc.)
Powerline communication technologies (HomePlug GP, Auto-Rem)
Ethernet (in parking lots)
Optical Communications (Fi-Wi)
Architectures and Models for Grid-to-Vehicle Applications: Charging Control
Queuing models for charging control
Admission control techniques for electric vehicle charging
Network calculus for electric vehicles: Battery calculus
Optimization-based charging control approaches
Architectures and Models for Vehicle-to-Grid Applications
Aggregator controlled V2G for regulation
Distribution system controlled energy trading via electric vehicles
V2G to supply home appliances and compensate for brownouts
Inter-Vehicle Communications for Electric Vehicles
Electric vehicle to Road Side Unit (RSU) communications for electric vehicle monitoring
VANET server controlled charging station reservation
The role of Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environments (WAVE) in Connected Electric Vehicles
Electric Vehicle and Smart Grid Advanced Application Testbeds
BCIT smart microgrid and electric vehicle testbed
Singapore government electric vehicle testbed
Illinois Institute of Technology electric vehicle testbed
The University of California, Irvine (UCI) microgrid
Open Issues and Future Directions
Primary Audience Utility operators, telecom operators, electric vehicle OEMs, electric vehicle service providers, researchers and students are among the target audience. The audience is expected to gain in depth knowledge on electric vehicles and the smart grid, master the challenges and opportunities in electric vehicle charging and discharging in the smart grid, learn the cutting-edge science and technology that address those challenges and advance the opportunities. The audience will be armed with broad understanding of electric vehicle research and technology with examples.
Novelty This is the first tutorial in this area to cover a comprehensive background on electric vehicles, batteries, electric vehicle supply equipment types, charging properties, in addition to fundamentals of operation of the generation, transmission and distribution in the smart grid. It is also the first to provide essential tools to understand the fundamentals of electric vehicles, their interaction with the smart grid and introduce the state-of-the-art architectures, models and networks for the electric vehicle infrastructure.
Biography Dr. Hussein T. Mouftah is a Distinguished University Professor and Senior Canada Research Chair in Wireless Sensor Networks at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He has been with the ECE Dept. at Queen's University (1979-2002), where he was prior to his departure a Full Professor and the Department Associate Head. He has six years of industrial experience mainly at Bell Northern Research of Ottawa (then known as Nortel Networks). He has been a Distinguished Speaker of the IEEE Communications Society (2000-2008). He is the author or coauthor of 10 books, 65 book chapters and more than 1400 technical papers, 14 patents and 143 industrial reports. He is the joint holder of 20 Best Paper and/or Outstanding Paper Awards. He has received numerous prestigious awards. Dr. Mouftah is a Fellow of the IEEE (1990), the Canadian Academy of Engineering (2003), the Engineering Institute of Canada (2005) and the Royal Society of Canada RSC Academy of Science (2008).
Dr. Melike Erol Kantarci is an assistant professor at the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY. Previously, she was the coordinator of the Smart Grid Communications Lab and a postdoctoral fellow at the School of Electrical Engineering and Computer Science, University of Ottawa, Canada. She received the Ph.D. and M.Sc. degrees in Computer Engineering in 2009 and 2004, respectively. During her Ph.D. studies, she was a Fulbright visiting researcher at the Computer Science Department of the University of California Los Angeles (UCLA). She received the B.Sc. degree from the Department of Control and Computer Engineering at the Istanbul Technical University, in 2001. She has received a Fulbright PhD Research Scholarship (2006) and the Siemens Excellence Award (2004), and she has won two Outstanding/Best Paper Awards.
Abstract—The fifth-generation (5G) is coming. Quo vadis 5G? What architectures, network topologies and technologies will define 5G? Are methodologies to the analysis, design and optimization of current cellular networks still applicable to 5G? The proposed tutorial is intended to offer a comprehensive and in-depth crash course to communication professionals and academics. It is aimed to critically illustrate and discuss essential and enabling transmission technologies, communication protocols and architectures that are expected to make 5G mobile communications a reality.
Tutorial Objectives At present, no precise definition for 5G is available. Experts vary in opinion whether the cellular network of tomorrow will continue to enhance (peak) service rates further, or will focus on spectral efficiency enhancements, or will move to newer metrics such as energy efficiency, or even will define new metrics around the user quality of experience. According to the 5G Public-Private Partnership (5GPPP), 5G systems need to be capable of providing 1000 times higher capacity and a 90% reduction in energy consumption compared to today standards, in order to cope with the impressive increase of mobile data traffic and to reduce the ever increasing carbon emission footprint of mobile communications.
These expected targets require the definition and the optimization of radically-changing architectures and technologies, thus leading to a wholesale re-thinking of cellular operational principles & architectures, network topologies, transmission technologies and methods to their analysis, design and optimization.
No matter what the eventual metrics or systems will be, it is apparent that 5G cellular networks are coming. The fundamental questions, however, that nobody is currently capable of answering are: What architectures, topologies and technologies will define 5G? What methodologies shall be used for their analysis, design and optimization?
Most likely, no single architecture and technology will be capable of meeting all the requirements of 5G networks, as a function of the requested quality of service, user-experience, desired performance, hardware & signal processing complexity constraints and channel conditions. In light of that, and in stark contrast with previous generations of cellular networks that were characterized by fixed radio parameters and spectrum blocks, 5G networks will be allowed to opportunistically utilize never used frequency bands and to exploit multiple technologies for guaranteeing the best delivery of services to the end users. As such, there is general consensus that 5G will not be a mere evolution (just another generation) of the status quo, but it will need radical and disruptive changes in its architectures, topologies and technologies.
Such a fundamental and radical paradigm-shift in network design and architecture requires cross-sectoral skills & background, which can very unlikely be realized by researchers that have not received personalized training on innovative technologies and adequate methodological tools to their analysis.
The fundamental learning objective of this tutorial is to offer to academic and industrial researchers, graduate students and professors a crash course on essential elements that are expected to significantly shape next generation mobile cellular systems. The specific learning objectives of this tutorial are to develop a thorough understanding of:
the state of the art
current research activities
theoretical & practical issues
opportunities for research & development of essential elements for 5G communications
On the following main topics:
5G requirements, potential architectures and network topologies
large-scale multi-antenna systems
millimeter-wave communications and wideband channel modeling
decentralized cell-less cellular architectures
hyper-dense cellular network deployments and related tools to their analysis, design and optimization
The Path Towards 5G Communications (Speaker: Christos Verikoukis)
5G worldwide research activities
5G potential architectures and network topologies
5G standardization efforts
Massive MIMO (Speaker: Emil Björnson)
What is Massive MIMO and how does it work?
Propagation in massive MIMO
Research challenges and opportunities
Common myths and misconceptions
5G Channel Models (Speaker: Cheng-Xiang Wang)
5G channel model requirements
Massive MIMO and mmWave channel models
Channel models for high-mobility wireless systems
A unified 5G channel model framework
Energy-Efficient Distributed Cellular Systems (Speaker: Eduard Jorswieck)
Non-cooperative games and distributed implementation
Resource allocation for energy-efficient single-hop MIMO interference channels
Resource allocation for energy-efficient multi-hop multi-user multi-antenna interference networks
Ultra-Dense Heterogeneous Cellular Networks Modeling and Analysis (Speaker: Marco Di Renzo)
From the grid to point processes: Why stochastic geometry modeling of ultra-dense cellular networks?
Enabling mathematical tools and fundamental results
Stochastic geometry modeling and analysis of uWave MIMO-aided cellular networks
Stochastic geometry modeling and analysis of mmWave MIMO-aided cellular networks
Primary Audience Students, academic researchers, industry affiliates and individuals working for government, military, science and technology institutions who would like to learn about emerging 5G architectures, transmission technologies, communication protocols and their achievable performance. The tutorial is intended to provide the audience with a complete overview of the potential benefits, research challenges, implementation efforts and applications of enabling 5G technologies. Due to the multi-faceted nature of the tutorial, all attendees working in wireless access technologies for 5G communications may be interested in attending the proposed tutorial.
Novelty The tutorial is proposed at a time where the technologies that are the core tenet of the tutorial are widely acknowledged as essential to meet 5G requirements, but, at the same time, are still at their R&D infancy, often partially understood by many and even misunderstood by few. The potential impact and importance of the tutorial lies in its multi-faceted nature: A view that conventional mono-topic tutorials are incapable of offering.
Biography Marco Di Renzo received the Ph.D. degree in Electrical and Information Engineering from the University of L’Aquila, Italy, in January 2007. Since January 2010, he has been a Tenured Academic Researcher with the French National Center for Scientific Research (CNRS), as well as a faculty member of the Laboratory of Signals and Systems (L2S), CNRS, SUPELEC, and the University of Paris-Sud XI, Paris, France. His main research interests are in the area of wireless communications theory and stochastic geometry.
Christos Verikoukis got his Ph.D. from the Technical University of Catalonia in 2000. He is currently the Head of the SMARTECH department at CTTC and an adjunct associate professor at Barcelona University. His area of expertise is in the design of energy efficient layer 2 protocols and RRM algorithms.
Emil Björnson received the Ph.D. degree in Telecommunications from the Department of Signal Processing at KTH Royal Institute of Technology, Sweden, in 2011. He is currently an Assistant Professor at Linköping University, Sweden. His research interests include multi-antenna cellular communications, massive MIMO techniques, radio resource allocation, green energy efficient systems and network topology design.
Eduard Jorswieck received his Doktor-Ingenieur (Ph.D.) degree from the Technische Universität Berlin, Germany, in 2004. Since February 2008, he has been the head of the Chair of Communications Theory and Full Professor at TUD, Germany. Dr. Jorswieck’s main research interests are in the area of signal processing for communications and networks.
Cheng-Xiang Wang received the PhD degree in Wireless Communications from Aalborg University, Denmark, in 2004. He has been with Heriot-Watt University, UK since 2005, and became a Professor in Wireless Communications in 2011. His main research interests are in the area of channel modeling for 5G cellular systems, with special emphasis on mmWave communications.
Abstract—Suppose that a 5G wireless network is designed from scratch to bring a uniform user experience with maximal energy efficiency (EE) as the main goal. How would such a network look like? To answer this fundamental question we need to understand how the EE depends on various network design parameters: the density and distribution of access points; the number of antennas deployed at each access point; the number of user terminals that can be served simultaneously; the beamforming that maps antennas to users; the average radiated signal power per user; and the hardware characteristics. In this tutorial, the EE metric [bit/Joule] is defined as the ratio between sum area throughput [bit/s/km^2] and area power consumption [Joule/s/km^2]. A survey is first provided on how to model these main terms accurately, to take all important system parameters and dependences into account. Based on the developed models, the EE is maximized using tools from both mathematical optimization and stochastic geometry. This leads to closed-form expressions that describe how the main design parameters depend on one another. The results and insights are exemplified for two tractable cases of network deployment: regular patterns of base stations (e.g., hexagonal cells) and stochastic patterns based on Poisson point processes. We will see how small cells and massive MIMO techniques show up naturally as energy-efficient solutions. In the last part of the tutorial, we describe how to optimize 5G networks with respect to more than one metric; for example, energy efficiency, user throughput, and area throughput.
Tutorial Objectives The audience will:
-- Acquire knowledge of which are the main performance metrics to consider when designing 5G networks.
-- Learn how to model the energy-efficiency with sufficient detail and what type of misinterpretations that commonly occur when the modeling is inaccurate.
-- Gain a basic knowledge of which analytical tools that can be used to optimize the energy-efficiency.
-- Learn how the energy-efficiency depends on various system design parameters: the number of antennas and users per access point; density of access points; radiated transmission power; hardware characteristics and circuit power; and so forth.
-- Learn which ranges of energy-efficiency that one can expect in future networks (e.g., tens of Mbit/Joule).
-- Gain a basic understanding of the concept of massive MIMO, how it can be deployed in future networks, and what are the current research challenges.
-- Learn which role that small cells can play in the development of energy efficient networks, and why small cells and massive MIMO complement one another.
-- Acquire basic knowledge of how user mobility inflicts fluctuations in the energy consumption and how a proper modeling can be utilized for improved network design.
-- Understand the basic concepts of multi-objective optimization and why this framework is the rigorous way of treating design problems with more than one performance metric, which is the case for 5G networks.
Introduction & Background
General Problem Formulation
Defining the Energy-Efficiency (EE) Metric
System Model, Beamforming, and Transmission Protocol
Deriving Detailed Rate and Power Consumption Expressions
Example: Why are Detailed Models Necessary?
Optimization of EE: Fixed Regular Deployment
Closed-Form Optimal System Parameters
Insights: Fundamental Interplay between Design Parameters
Numerical Results: Single-Cell and Multi-Cell
Basic Asymptotic Motivation
Main Properties and Deployment Ideas
Open Research Problems
Optimization of EE: Stochastic Deployment
Closed-Form Optimal System Parameters
Insights: Fundamental Interplay between Design Parameters
What is the Optimal Cell Density?
Impact of User Mobility
User Mobility Models
Methodology: Large System Analysis
Fluctuations of Energy Consumption in the Large System Limit
Application: Dimensioning of Batteries at Access Points
Optimizing Multiple Metrics at the Same Time
Single versus Multiple 5G Metrics
Methodology: Multi-Objective Optimization
A Posteriori Approach
A Priori Approach
Example: 5G Network Design
Primary Audience We believe that this tutorial will attract researchers from both academia and industry. Any researcher that takes part in the development of 5G networks will benefit from basic understanding of energy-efficiency and knowing the methodology for solving design problems with multiple objectives. We intend to spend 30-45 minutes on building up the basic models without requiring any background knowledge or advanced mathematical skills. Once the models have been developed, the tutorial will focus on conveying fundamental results, insights, and concepts.
Novelty We are at a point in time when researchers are trying to formalize their expectations and requirements for 5G communications. It is therefore important and timely to give a tutorial on the state-of-the-art of modeling, analyzing and optimizing the overall energy efficiency; in particular, since misleading conclusions can be drawn if the models are not accurate. Another novel part is to analyze massive MIMO and small cells in a joint framework that reveals how these concepts are complementing one another.
Biography Emil Björnson received the M.S. degree in Engineering Mathematics from Lund University, Sweden, in 2007. He received the Ph.D. degree in Telecommunications from KTH Royal Institute of Technology, Sweden, in 2011. 2012—July 2014, he was a joint postdoc at Supélec, Paris, France, and KTH Royal Institute of Technology. He is currently an Assistant Professor at Linköping University, Sweden. His expertise spans multi-antenna cellular communications, massive MIMO techniques, radio resource allocation and energy efficient networks. He is the first author of the book "Optimal Resource Allocation in Coordinated Multi-Cell Systems" from 2013. He is dedicated to reproducible research and published much simulation code. Dr. Björnson has received 4 best paper awards for novel research on optimization and design of multi-cell multi-antenna communications.
Luca Sanguinetti is an Assistant Professor in the Dipartimento di Ingegneria dell'Informazione of the University of Pisa, since 2005. He received the Telecommunications Engineer degree (cum laude) and the Ph.D. degree in information engineering from the University of Pisa, Italy, in 2002 and 2005, respectively. In 2004, he was a visiting Ph.D. student at the German Aerospace Center (DLR), Oberpfaffenhofen, Germany. June 2007—2008, he was a postdoctoral associate at Princeton. From July 2013 to June 2015, he is with Supélec, Paris, France. He is currently serving as an Associate Editor for IEEE Transactions on Wireless Communications. His expertise spans the areas of communications and signal processing, estimation and detection theory. Current research topics are dense deployments for green cellular networks, development of game-theoretic solutions for energy-efficient interference mitigation and analysis of the impact of user mobility in the energy consumption of wireless networks. He the co-recipient of best paper awards at WCNC 2013 and WCNC 2014. He is also the recipient of the FP7 Marie Curie IEF Grant Dense4Green "Dense deployments for green cellular networks".
Abstract—In this tutorial we will present the fundamental theory behind the design of a generic PHY layer software defined radio (SDR) and demonstrate the first principles implementation, design and real time operation of an SDR using off-the-air signal live in the tutorial. We will use the $20 RTL-SDR USB device which can produce 8 bit I/Q samples at up to 2.8MHz sampling rate and receive over the range 50MHz to almost 1.7GHz. As part of the tutorial we will build a first SDR implemented AM and then FM radio receiver, followed by implementations and demonstrations of 433MHz and 868MHz digital QAM receivers. We will also viewing some other signals around us (from IoT temperature sensors, mobile/wireless and so on). We will view all signals and build all components and designs from first principles DSP theory using MATLAB/Simulink and run real time on a standard Windows PC hosting MATLAB and drivers for the RTL-SDR. Attendees will receive a free USB RTL-SDR stick and access to all presented materials, instruction in, and use of full MATLAB/Simulink desktop and course notes including open versions of all of the SDR designs (and more) that were presented.
Tutorial Objectives The objectives of this tutorial are:
To introduce attendees to software defined radio implementations
To outline core DSP (digital signal processing) methods for physical layer SDR such as DDC (direct digital downconverter)
To present spectrum viewing applications showing desktop SDR using the RTL-SDR USB receiver and MATLAB/Simulink (GSM, 3G, LTE and other "on-air" nearby)
To introduce attendees to Simulink designs for SDR (no previous experience is necessary - designs are presented on a need-to-know basis)
To design and build a first principles AM and FM digital receiver, and a QPSK based digital receiver for a 433MHz in-lab transmission
To allow all attendees to design and build on a PC, using MATLAB/Simulink and an RTL-SDR USB stick and simple omni-antenna
To ensure all attendees are excited by the ease and low cost opportunity for SDR on the desktop.
1. Introduction to SDR—The Wireless Revolution is just beginning!
2. From Analog to Digital—The radio driven desire to sample at GHz
3. Design of an IF Software Defined Radio 100s of MHz to 10s of MHz IF to baseband
4. Digital Downconverter (DDC) DSP Design
5. The RTL-SDR Architecture—Analog Receiver and MHz Sampler
6. Receiving I/Q Signals at Baseband with the RTL-SDR
7. Hardware Support Package and integration to standard MATLAB/Simulink
8. Live Design and Demo: Design of a first SDR: AM radio Receiver at 433MHz
9. Live Design and Demo: Design of an SDR enabled FM radio receiver over 88-102MHz
10. Spectrum Viewing Demo: GSM spectra observation and viewing across the band
11. On-Air Mobile Decoding Demo: LTE Cell ID Extraction using MATLAB/Simulink
12. Desktop RF Tx and Rx Design: Multiplexing 8 audio channels for desktop FM Transmits and RTL-SDR receiver
13. First Principles SDR Design Example: Receiving a 433MHz 200kbits/sec QAM signal (Transmitted from a desktop USRP to RTL-SDR)
14. Working with AGC: Tuning, Digital Filtering, Synchronisation and Timing, Data Recovery
Primary Audience Aimed at academics, students and professional engineers interested in building and designing real time SDR implementations on the desktop from first principles. We aim to allow attendees to both build and design receivers, and also to observer on-the-air signals ranging from GSM, to FM radio, to 433MHz key fobs.
Novelty The tutorial will allow attendees to take live signals off the air, and implement real time SDR systems on the desktop in fixed point MATLAB implementations; all on a $20 receiver. The morning of the course would be lectures and demonstration (3 hours) and the afternoon of the course would be hands-on for all attendees (3 hours). A University of Strathclyde lab with up to 60 seats would be used for the hands-on - this will book and acquired by the presenters. (As such the limit on attendees would be 60.) Attendees will receive a free RTL-SDR USB, and a copy of all presented notes/slides, and all RTL-SDR examples.
Biography Bob Stewart is the MathWorks Professor of Signal Processing in the Department of Electronic and Electrical Engineering at the University of Strathclyde. He has more than 20 years of experience teaching DSP and communications to industry and student audiences.
Dr. Louise Crockett is an academic in the Department of Electronic and Electrical Engineering at the University of Strathclyde. Her current R&D work is with Xilinx FPGAs on the implementation of SDR and other DSP systems. She is also the lead author of the best selling text, The ZynqBook on FPGAs, jointly published with Xilinx in 2014.
Dr. Neil MacEwen is the technical lead on Software Defined Radio at the MathWorks Glasgow Office and has extensive experience on design of SDR radio based systems. He was awarded his PhD in 2008 for work on OFDM receivers.