V2X communications are expected to bring in a series of far-reaching benefits for transformative changes to our society such as significantly improved roadway safety and efficiency, drastically reduced traffic jams and carbon monoxide emission, as well as optimized routes and unprecedented travel experiences. With 5G networks starting to roll out and the 6G research just begun, V2X, as one of the most promising vertical industries, has attracted tremendous investment worldwide and will be a game changer which opens the door to numerous opportunities for new services and businesses. A major objective of this workshop is to bring together state-of-the-art innovations, research activities (both in academia and industry), and the corresponding standardization impacts of V2X for the next generation intelligent transportation systems, so as to understand the inspirations, requirements, and the promising technical options to boost and enrich activities in the area of V2X. The scope of workshop includes (but not limited to) the following topics:
- V2X resource allocation and management;
- V2X communication and networking for Internet of Vehicles (IoV);
- Artificial intelligence and machine learning for V2X system optimization and decision making;
- Coding, modulation, and signal processing for high mobility communications such as orthogonal time-frequency space (OTFS);
- Training sequence and waveform design over doubly selective channels;
- Grant-free V2X communications for ultra-low latency;
- Mission critical V2X communications such as ultra-reliable low-latency communications (URLLC);
- Non-orthogonal multiple access (NOMA) such as sparse-code multiple access (SCMA) and resource spread multiple access (RSMA) for densely connected V2X networks;
- Cross-layer optimization for V2X communication and networking;
- Full duplex (FD) radios for V2X Communication;
- Cloud/edge/fog/dew computing and applications/services for V2X networks;
- UAV-assisted V2X communications;
- Cellular V2X with 5G New Radio and beyond;
- Dedicated short-range communications (DSRC) and its evolution;
- Hybrid V2X networks with RF and visible light communications (VLC);
- Network slicing for V2X networks;
- Security issues and designs for V2X (e.g., physical layer security, blockchain based wireless networks);
- Standardizations, use-cases, field-trials, prototypes, deployment and performance evaluation of V2X.
- Zilong Liu, School of Computer Science and Electronics Engineering, University of Essex, UK.
- Vivek Bohara, Department of Electronics and Communications Engineering, IIIT-Delhi, India.
- Anand Srivastava, Department of Electronics and Communications Engineering, IIIT-Delhi, India.
- Pei Xiao, 5G Innovation Centre, University of Surrey, UK.
- Md. Noor-A-Rahim, School of Computer Science and IT, University College Cork, Ireland.
- Zhengguo Sheng, Department of Engineering and Design, University of Sussex, UK.
- Paper Submission: 8 Nov, 2020
- Notification of Acceptance: 16 Nov, 2020
- Final Submission: 25 Nov, 2020
Submission Link : https://edas.info/newPaper.php?c=27510&track=104081
Title: OTFS – A Modulation Scheme for High-Mobility Environments
Speaker: Prof. A. Chockalingam, IISc, India
Bio: Dr. A. Chockalingam He received the B.E. (Hons.) degree in electronics and communication engineering from the P.S.G College of Technology, Coimbatore, India, in 1984, the M.Tech degree in electronics and electrical communication engineering (with specialization in satellite communications) from IIT Kharagpur, India, in 1985, and the Ph.D degree in electrical communication engineering (ECE) from the Indian Institute of Science (IISc), Bangalore, India, in 1993. From 1986 to 1993, he was with the Transmission Research and Development Division, Indian Telephone Industries Limited, Bangalore. From 1993 to 1996, he was a Post-Doctoral Fellow and an Assistant Project Scientist with the Department of Electrical and Computer Engineering, University of California at San Diego, CA, USA. From 1996 to 1998, he was with Qualcomm, Inc., San Diego, as a Staff Engineer/Manager with the Systems Engineering Group. Since 1998, he has been with the faculty of the Department of ECE, IISc, Bangalore, where he is currently a Professor, involved in wireless communications research. Dr. Chockalingam is a Fellow of the Indian National Academy of Engineering; the National Academy of Sciences, India; the Indian National Science Academy; and the Indian Academy of Sciences. He received the Swarnajayanti Fellowship and the J. C. Bose National Fellowship from the Department of Science and Technology, Government of India. He served as an Associate Editor for the IEEE Transactions on Vehicular Technology, an Editor for the IEEE Transactions on Wireless Communications, and a Guest Editor for the IEEE Journal on Selected Areas in Communications and the IEEE Journal of Selected Topics in Signal Processing (Special Issue on Soft Detection on Wireless Transmission). He is an author of the book on `Large MIMO Systems’ published by Cambridge University Press.
Abstract: Orthogonal time frequency space (OTFS) modulation is a recently proposed modulation scheme suited for high-mobility environments. It is a 2-dimensional modulation scheme designed in the delay-Doppler (DD) domain, unlike traditional modulation schemes which are designed in the time-frequency (TF) domain. OTFS multiplexes the information symbols in the DD domain, whereas conventional multicarrier modulation schemes multiplex symbols in the TF domain. Also, the channel response is viewed in the DD domain as opposed to viewing it in the TF domain. An advantage of the DD representation of wireless channels is that the rapid fluctuations in time-varying channels exhibit slow variations when viewed in the DD domain. This, along with the fact that the channel in the DD domain has a sparse nature, simplifies channel estimation in rapidly time-varying channels. Several studies in the literature have reported superior performance of OTFS compared to OFDM, generalized frequency division multiplexing (GFDM), and single-carrier FDMA (SC-FDMA) in high-mobility/high-Doppler environments, making OTFS attractive for use cases such as V2X, high-speed train, and mmWave communications. This talk will introduce OTFS and highlight some of the detection, channel estimation, PAPR, and multiple access aspects of OTFS.
Title: From Connected vehicles to Internet-of-Things (IoT): Recent Advances in Communications and Networking
Speaker: Dr Zhengguo Sheng, Sussex University, UK.
Bio: Zhengguo Sheng has been a Senior lecturer in the Department of Engineering and Design at University of Sussex since 2018. He received his Ph.D. and M.S. with distinction at Imperial College London in 2011 and 2007, respectively, and his B.Sc. from the University of Electronic Science and Technology of China (UESTC) in 2006. From 2013 to 2014, he was a research associate in the Department of Electrical and Computer Engineering at University of British Columbia (UBC), Canada. From 2011 to 2013, he was with France Telecom Orange Labs as the senior researcher and project manager in M2M/IoT. During 2009, he also worked as a research intern with IBM T. J. Watson Research Center, USA, and U.S. Army Research Labs. His current research interests cover connected vehicles, Internet-of-Things (IoT), and cloud/edge computing. He has published over 100 journal and conference papers, 5 books, 1 patent and 2 standards contribution in OneM2M and OMA LWM2M. His current research works are funded by H2020, EPSRC, Royal Society and University of Sussex. He is also the receipt of Emerging research award 2017 from University of Sussex.
Abstract: Modern cars feature embedded systems that monitor and manage all the critical sensors and actuators. The in-vehicle connectivity can be further extended with Vehicle-to-Everything (V2X) technology, which allows cars to exchange that collected information and even act on it. Meanwhile, IoT will increase the pervasiveness of the Internet and the overall connectivity by integrating every “object” (e.g., sensors, smart phones, vehicles, infrastructures and external management platform) forming a fully connected system. By developing mission-critical and intelligent communications and networking capabilities, the combination of vehicles and IoT have the potential to reach a wide range of objectives at more cost effective ways.
Title: Mobility for Tomorrow: Connected and Autonomous Vehicle Perspective
Speaker: Prof G. G. Md. Nawaz Ali
Bio: G. G. Md. Nawaz Ali (IEEE M’15) received his B.Sc. degree in Computer Science and Engineering from the Khulna University of Engineering & Technology, Bangladesh in 2006, and the Ph.D. degree in Computer Science from the City University of Hong Kong, Hong Kong in 2013 with the Outstanding Academic Performance Award. He is currently working as an Assistant Professor with the Department of Applied Computer Science of the University of Charleston, WV, USA. Prior to joining UCWV, he was a Post-doctoral Fellow with the Department of Automotive Engineering, The Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA from March 2018 to July 2019. From October 2015 to March 2018, he was a postdoctoral research fellow with the School of Electrical and Electronic Engineering of Nanyang Technological University (NTU), Singapore. He is a reviewer of a number of international journals including the IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS AND MAGAZINE, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, IEEE INTERNTET OF THINGS (IOT) JOURNAL, IEEE ACCESS, AND Wireless Networks etc. His current research interests include Vehicular Cyber Physical System (VCPS), wireless broadcasting, mobile computing, and network coding.
Abstract: In this talk, I will briefly discuss on my work and role in Connected and autonomous vehicle for energy efficient project with the Department of Automotive Engineering of Clemson University, SC, USA. Our objective is to save energy, reduce braking events, and harmonize traffic in connected and automated vehicles. In the course of this US DOE (Department of Energy) project, we want to demonstrate a minimum of 10% energy savings in mixed traffic streams of human-driven and Connected and Autonomous Vehicles (CAVs). Next, I will share my recent experience of ‘US 16 million dollar, Smart, Intelligent’ and ‘24/7 live’ V2X Test Bed in NTU campus (Nanyang Technological University, Singapore), named as NTU-NXP Smart Mobility Test Bed (SMTB) for advancing the capabilities in ITS (Intelligent Transportation System). The goals of SMTB are: to support real-life field testing of future mobility and ITS applications; to provide a permanent infrastructure for ITS players; to develop, test and verify their technologies and products; and to establish best practices for use of ITS technologies with world wide applications. I will discuss on test-bed infrastructure, used major V2X (Vehicle-to-everything) wireless technologies, software resources and data analytics.
Title: Machine Learning as a promising technology for V2X
Speaker: Dr Haeyoung Lee
Bio: Haeyoung Lee is currently a research fellow at 5G Innovation Centre, University of Surrey in UK, since 2016. She obtained her MSc degree in Information and Communication Engineering from Gwangju Institute of Science and Technology in Korea. Then, she joined Samsung Electronics in 2004, and researched and developed about mobile internet platforms for CDMA systems. From 2006 to 2015, she worked as a policy and research officer at national radio research agency (RRA) in the Ministry of Science, ICT and future planning (MISP), which is spectrum regulator of Korea. She contributed to standarisation activities for spectrum harmonisation and dynamic spectrum use in ITU-R and IEEE 802.22. She was a co-organiser of international workshop on 5G/B5G in ICTC 2018 in Korea. She received her PhD degree in Centre for Communication System Research at University of Surrey in 2015. She has worked many EU projects including OneFIT, Speed5G, Clear5G, and 5G-HEART. Her current research interests include flexible spectrum use, optimisation of radio resource management and machine learning applications for future wireless communication.
Abstract: Recent advances in machine learning research with the availability of large datasets and storage, and high computational power have enabled various novel technologies. Especially, employing machine learning into vehicular communication is envisaged to pave the way towards the future intelligentisation in 6G vehicular networks which are highly dynamic and versatile to meet various application requirements. While machine learning is capable of extracting the characteristics and identifying the relationship between input and output data, machine learning can be utilized as a promising alternative to conventional mathematical approaches to model wireless systems. For example, in the highly dynamic vehicular networks, machine learning is envisioned to enable real-time analysis and automated zero touch control for minimal human intervention in radio configuration. In this talk, major potentials, challenges, and the vision of ML for vehicular networks are discussed from the aspects of the physical layer and radio resource management.