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IEEE Vehicular Technology Magazine
Journal Prestige (SJR): 0.867

Citation Impact (citeScore): 5
Number of Followers: 7

Full-text available via subscription

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ISSN (Print) 1556-6072
Published by IEEE

[228 journals]

VTC2022-Spring
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  Abstract: Presents information on the VTC2022-Spring conference.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Staff List
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  Pages: 2 - 2
  Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Welcome to the June 2022 Issue [From the Editor]
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  Authors: Javier Gozalvez;
  Pages: 3 - 3
  Abstract: This issue of IEEE Vehicular Technology Magazine includes two special issues about topics of high interest to the IEEE Vehicular Technology Society. The first offers a selection of seven articles on backscatter and reconfigurable intelligence surfaces (RISs) for wireless communication in future 6G. RISs can reconfigure the propagation environment by using passive reflecting elements. This opens the door to low-cost and low-energy solutions that help customize wireless channels based on coverage needs and other criteria. Ambient backscatter communication does not need active radio-frequency components and can be deployed at large scale with low cost since it can harvest energy.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
The Lively Versatility of the 5G Ecosystem [Mobile Radio]
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  Authors: Claudio Casetti;
  Pages: 4 - 13
  Abstract: Solution testing, platform trialing, the showcasing of demos, and proofs of concept (PoCs) all are mainstays of emerging technologies, and 5G is no exception, even while its commercial rollout is already in full swing all around the world. Thanks to the versatility of the 5G ecosystem, trialing efforts are focusing on multiple areas ranging from enhanced, interactive mobile phone calls to revisited concepts in virtual radio access network (RAN) and edge computing architectures. Offering a prime stage is the 2022 Mobile World Congress (MWC), in Barcelona, returning to its consolidated large-scale, in-person format after two years of the pandemic.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
June 2022 Land Transportation News [Transportation Systems]
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  Authors: Bih-Yuan Ku;
  Pages: 10 - 13
  Abstract: On 30 November 2021, VIA Rail and Siemens unveiled new passenger train sets for numerous services departing Toronto, beginning in 2022. The trains are pulled by slick new Siemens Charger locomotives, basically the de facto standard new intercity rail locomotive in North America. VIA’s Charger is a variant, known as the SC-42, and has a distinct design that looks better than most of the railroad’s trains, as shown in Figure 1. The units are capable of speeds up to 200 km/h, or 125 mi/h, although VIA won’t be operating that fast on current services, largely due to track quality. Yet, the improved performance of the new fleet will help upgrade service speeds by about 5% to reduce trip times.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Backscatter and Reconfigurable Intelligent Surface-Empowered Wireless
Communications in 6G [From the Guest Editors]
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  Authors: Cunhua Pan;Marco Di Renzo;Chau Yuen;Derrick Wing Kwan Ng;Ertugrul Basar;
  Pages: 14 - 15
  Abstract: Now that the 5G mobile network system is rolling out worldwide, extensive research attention has shifted to the next technology, 6G, in academia and industry. Exciting new applications, such as multisensory extended reality applications, connected robotics and autonomous systems, and brain–computer interactions, will be supported by 6G communications. These pose new challenges through their data rate, latency, connectivity density, and energy efficiency requirements, which cannot not be satisfied by 5G.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Multiwideband Terahertz Communications Via Tunable Graphene-Based
Metasurfaces in 6G Networks: Graphene Enables Ultimate Multiwideband THz
Wavefront Control
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  Authors: Hamidreza Taghvaee;Alexandros Pitilakis;Odysseas Tsilipakos;Anna C. Tasolamprou;Nikolaos V. Kantartzis;Maria Kafesaki;Albert Cabellos-Aparicio;Eduard Alarcón;Sergi Abadal;
  Pages: 16 - 25
  Abstract: The next generation of wireless networks is expected to tap into the terahertz (THz) band (0.1–10 THz) to satisfy the extreme latency and bandwidth density requirements of future applications. However, the development of systems in this band is challenging as THz waves confront severe spreading and penetration losses, as well as molecular absorption, which leads to strong line-of-sight requirements through highly directive antennas. Recently, reconfigurable intelligent surfaces (RISs) have been proposed to address issues derived from non-line-of-sight (non-LoS) propagation, among other impairments, by redirecting the incident wave toward the receiver and implementing virtual-line-of-sight communications. However, the benefits provided by a RIS may be lost if the network operates at multiple bands. In this article, the suitability of the RIS paradigm in indoor THz scenarios for 6G is assessed grounded on the analysis of a tunable graphene-based RIS that can operate in multiple wideband transparency windows. A possible implementation of such a RIS is provided and numerically evaluated at 0.65/0.85/1.05 THz separately, demonstrating that beam steering and other relevant functionalities are realizable with excellent performance. Finally, the challenges associated with the design and fabrication of multiwideband graphene-based RISs are discussed, paving the way to the concurrent control of multiple THz bands in the context of 6G networks.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Reconfigurable Intelligent Surface (RIS)-Aided Vehicular Networks: Their
Protocols, Resource Allocation, and Performance
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  Authors: Yuanbin Chen;Ying Wang;Jiayi Zhang;Ping Zhang;Lajos Hanzo;
  Pages: 26 - 36
  Abstract: Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving. Having said that, the 3rd Generation Partnership Project (3GPP) faces numerous open challenges concerning the RIS-aided vehicle-to-everything (V2X) solutions of the near future. To tackle these challenges and to stimulate future research, this article focuses on the prospective transmission design of RIS-aided V2X communications. In particular, two V2X sidelink modes are enhanced by exploiting RISs and their variants, followed by a customized transmission frame structure that partitions the transmission efforts into different phases. Next, effective channel-tracking and resource allocation techniques are developed for attaining a high beamforming gain at low overhead and complexity. Finally, promising research topics are highlighted, and future 3GPP standardization items are proposed for RIS-aided V2X systems.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Location Awareness Via Intelligent Surfaces: A Path Toward Holographic NLN
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  Authors: Moe Z. Win;Ziyi Wang;Zhenyu Liu;Yuan Shen;Andrea Conti;
  Pages: 37 - 45
  Abstract: Location information is critical for numerous applications, such as smart cities, autonomous vehicles, and Industry 4.0. In this article, we present the paradigm of holographic network localization and navigation (NLN), namely NLN with holographic radios. We describe holographic NLN enabled by reconfigurable intelligent surfaces (RISs), where the phase responses of the RISs are controlled to create desirable electromagnetic (EM) environments for wireless communications. Specifically, we present a mathematical model for signal transmission and reception in the presence of RISs. This model applies to both continuous intelligent surfaces (CISs) and discrete intelligent surfaces (DISs) and accounts for the polarization and directivity of antennas. We review recent research progress on RISs and summarize their characteristics that benefit communication and localization. We present key ingredients of NLN and describe how RISs can be employed to enable holographic NLN. We quantify the performance of RIS-enabled holographic NLN with a case study, showing that RISs can significantly improve localization accuracy, especially in scenarios where line-of-sight (LOS) paths between agents and anchors are obstructed.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Simultaneously Transmitting and Reflecting Intelligent Omni-Surfaces:
Modeling and Implementation
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  Authors: Jiaqi Xu;Yuanwei Liu;Xidong Mu;Joey Tianyi Zhou;Lingyang Song;H. Vincent Poor;Lajos Hanzo;
  Pages: 46 - 54
  Abstract: Given the rapid development of advanced electromagnetic (EM) manipulation technologies, researchers have turned their attention to the investigation of smart surfaces for enhancing radio coverage. Simultaneously transmitting and reflecting (STAR) intelligent omni-surfaces (IOSs) constitute one of the most promising categories. Although previous research contributions have demonstrated the benefits of simultaneously transmitting and reflecting intelligent omni-surfaces (STAR-IOSs) in terms of wireless communication performance gains, several important issues remain unresolved, including practical hardware implementations and accurate physical models. In this article, we address these by discussing four practical hardware implementations of STAR-IOSs as well as three hardware modeling techniques and five channel modeling methods. We thus clarify the taxonomy of smart surface technologies in support of further investigating the family of STAR-IOSs.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Joint Optimization of IRS and UAV-Trajectory: For Supporting Statistical
Delay and Error-Rate Bounded QoS Over mURLLC-Driven 6G Mobile Wireless
Networks Using FBC
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  Authors: Xi Zhang;Jingqing Wang;H. Vincent Poor;
  Pages: 55 - 63
  Abstract: Massive ultra-reliable and low-latency communications (mURLLC) has been developed as a new and dominating 6G-standard services to support statistical quality of service (QoS) provisioning while raising several major design issues, including massive connectivity, ultra-low latency, and super-reliability. Correspondingly, a number of emerging 6G candidate enablers, including statistical delay and error-rate bounded QoS provisioning, finite blocklength coding (FBC), intelligent reflecting surfaces (IRS), unmanned aerial vehicle (UAV), etc., have been developed to support mURLLC. Specifically, due to the potential improvements in coverage capability as well as the spectral efficiency, both IRS and UAV have been widely proposed to reconfigure wireless propagation environments to compensate for blocked line-of-sight (LOS) communication links and create controllable and smart radio environments. In addition, to solve the massive connectivity issues imposed by mURLLC, integrating UAV with IRS provides a promising means to significantly enhance LOS coverage due to the relatively high altitude and 3D mobility of the UAVs. However, although small-packet communications enabled by FBC are usually employed for massive access to reduce access latency and decoding complexity, how to upper-bound both delay and error rate while efficiently supporting mURLLC in IRS-UAV-integrated systems still remains a challenging problem.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Channel Estimation Techniques for RIS-Assisted Communication:
Millimeter-Wave and Sub-THz Systems
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  Authors: Song Noh;Junse Lee;Gilwon Lee;Kyungsik Seo;Youngchul Sung;Heejung Yu;
  Pages: 64 - 73
  Abstract: Millimeter-wave (mm-wave) and sub-terahertz (sub-THz) communications are expected to be one of the biggest beneficiaries of the emerging reconfigurable intelligent surface (RIS) technology. RISs can compensate for large path loss and blockage inherent to the mm-wave and sub-THz frequency bands to yield enhanced communication performance in these bands. To achieve high beamforming gain and realize the enhanced performance in RIS-assisted wireless communication, the acquisition of accurate channel state information (CSI) is critical. In this article, we provide an overview of channel estimation for RIS-assisted mm-wave/sub-THz communication to address technical challenges, tradeoffs, channel estimation frameworks, and training signal design. We summarize the recent RIS-related sparse channel estimation approaches based on beam-space, sparse recovery, array signal processing, and data-driven techniques, highlighting several challenges for future research.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Reconfigurable Intelligent Surface Empowered Optimization for Spectrum
Sharing: Scenarios and Methods
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  Authors: Zhong Tian;Zhengchuan Chen;Min Wang;Yunjian Jia;Linglong Dai;Shi Jin;
  Pages: 74 - 82
  Abstract: The reconfigurable intelligent surface (RIS) has the capability to reconstruct the radio environment of wireless channels, which can alleviate the interference in the spectrum-sharing system (SSS). In this article, the current research directions of the RIS-aided SSS and the proposed methods of the joint optimization about passive beamforming of the RIS and the active beamforming of the access points are summarized and analyzed to obtain good insight into this technique. The RIS can improve the spectral efficiency (SE) and energy efficiency (EE) even in complicated scenarios, such as the SSS coexisting with multiple primary networks (PNs) or several secondary networks (SNs). The simulation results indicate that the deployment of the RIS and the varying number of reflecting elements on the RIS have significant impact on the gain of the RIS brought in the SSS. Although the RIS-aided SSS has some challenges including the discretization of reflecting coefficients on the RIS, it still has huge potentials to be utilized in diverse fields such as vehicular or unmanned aerial vehicles (UAVs) communications.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Artificial Intelligence for Autonomous Vehicular Communication Networks
[From the Guest Editors]
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  Authors: Li-Chun Wang;Haris Gačanin;Dusit Niyato;Yu-Jia Chen;Chun-Hung Liu;Alagan Anpalagan;
  Pages: 83 - 84
  Abstract: With advances in sensing, communication, and networking, autonomous vehicles and unmanned aerial vehicles (UAVs) are expected to play a vital role in a variety of areas, including health care, Industry 4.0, smart farming and agriculture, logistics, transportation, and public safety. Together with the upcoming 5G/6G technologies, connected vehicular systems will become more ubiquitous and practical. Artificial intelligence (AI) and machine learning (ML) can provide significant benefits toward automating the tasks of sensing, computing, and communicating in vehicular communication networks. By leveraging traces of numerous operations, AI can optimize network decisions that are reflected in resource utilization and service enhancement.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Deep Reinforcement Learning-Based Resource Management for Flexible Mobile
Edge Computing: Architectures, Applications, and Research Issues
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  Authors: Kezhi Wang;Liang Wang;Cunhua Pan;Hong Ren;
  Pages: 85 - 93
  Abstract: In this article, we introduce autonomous vehicle-assisted mobile edge computing (AV-MEC), including unmanned ground vehicle (UGV)- and unmanned aerial vehicle (UAV)-assisted MEC, where the UAV/UGV can be deployed and carry the computing server to serve ground mobile devices (MDs). We first discuss applications and main research problems. Then, deep reinforcement learning (DRL)-based solutions are introduced, explored, and demonstrated. We also discuss challenges and future research directions for an AV-MEC system with DRL being applied to it.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
An Energy-Efficient Intelligent Framework of UAV-Enhanced Vehicular
Networks: Open Problems and a Case Study
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  Authors: Shu Fu;Liuguo Yin;Chunxiao Jiang;Abbas Jamalipour;
  Pages: 94 - 102
  Abstract: As the heterogeneous service requirements in vehicular networks (VNs) increase, caching, computing, and communication (3C) resources should be dynamically allocated. Unlike a traditional cellular wireless network with a fixed topology among base stations (BSs), unmanned aerial vehicles (UAVs) can constitute an energy-efficient rearrangeable wireless network serving VNs. The 3C resource allocation and UAV-based wireless network topology can be adaptively adjusted according to the service requirements of VNs by appropriate artificial intelligence (AI) algorithms. Although AI algorithms have been well studied in wireless networks, an energy-efficient intelligent frame for UAV service and arrangement should be further investigated.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Collaborative Driving: Learning-Aided Joint Topology Formulation and
Beamforming
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  Authors: Yao Zhang;Changle Li;Tom H. Luan;Chau Yuen;Yuchuan Fu;
  Pages: 103 - 111
  Abstract: Currently, autonomous vehicles are able to drive more naturally based on the driving policies learned from millions of driving miles in real environments. However, to further improve the automation level of vehicles is a challenging task, especially in the case of multivehicle cooperation. In recent heated discussions of 6G, millimeter-wave (mm-wave and terahertz (THz) bands are deemed to play important roles in new radio communication architectures and algorithms. To enable reliable autonomous driving in 6G, in this article, we envision collaborative autonomous driving, a new framework that jointly controls driving topology and formulate vehicular networks in the mm-wave/THz bands. As a swarm-intelligence system, the collaborative driving scheme goes beyond existing autonomous driving patterns based on single-vehicle intelligence in terms of safety and efficiency. With efficient data sharing, the proposed framework is able to achieve cooperative sensing and load balancing so that improve sensing efficiency with saved computational resources. To deal with the new challenges in the collaborative driving framework, we further illustrate two promising approaches for mm-wave/THz-based vehicle-to-vehicle (V2V) communications. Finally, we discuss several potential open research problems for the proposed collaborative driving scheme.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Legislation Supports Autonomous Vehicles But Not Connected Ones [Connected
and Automated Vehicles]
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  Authors: Elisabeth Uhlemann;
  Pages: 112 - 115
  Abstract: It is inspiring to notice that legislation that helps incorporate autonomous vehicles on our roads in the near future is moving forward. The National Highway Traffic Safety Administration (NHTSA), which is part of the U.S. Department of Transportation (USDoT), has integrated automated vehicles into the existing safety standards such that the text in the standards do not rely on the existence of steering wheels and driver’s seats, which may not exist in fully autonomous vehicles. In addition, the NHTSA has incorporated lane-keeping support, pedestrian automatic emergency braking, blind spot detection, and blind spot intervention into its Five-Star Safety Ratings program. Such driver-assistance technologies are the first steps toward fully autonomous vehicles but, more importantly, toward safer ones. Developing safer vehicles requires significant investments, so it is important that the legislation provide a framework that is predictable, reducing the risk of long-term commitment.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
IEEE VPPC 2022
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  Pages: 115 - 115
  Abstract: Presents information on the IEEE VPPC 2022 conference.
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)
Initiatives for Wireless Channel Sounding Standards in IEEE [Standards]
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  Authors: Edward Au;
  Pages: 116 - 116
  Abstract: The synthetic aperture is a signal processing technique that collects signal samples across a spatial volume and generates a huge database that helps solve a wide array of problems. For example, a synthetic aperture radar (SAR) synthesizes the motion of a long antenna by combining received signals as it moves along a flight track and provides data with finer spatial resolution that help create 2D images and the 3D reconstruction of objects. Recently, the synthetic aperture has also applied to wireless channel sounding and the over-the-air calibration of wireless devices [1].
  PubDate: June 2022
  Issue No: Vol. 17, No. 2 (2022)