Javier Gozalvez
Editor-in-Chief
This issue of IEEE Vehicular Technology Magazine includes the first special issue looking into the application of the metaverse to connected and automated mobility. The metaverse is expected to interconnect the physical and digital worlds, and its application to the vehicular domain is fostered by the increasing softwarization of vehicles, augmented processing and sensing capabilities, and the pervasive direct and network-based connectivity of vehicles. This opens the door for novel applications that can exploit the large amounts of data collected by vehicles and their processing capability as well as the benefits of immersive applications, among others, for improving driving safety, efficiency, and comfort. I would like to thank our guest editors, Pengyuan Zhou, Lik Hang Lee, Zhi Liu, Hang Qiu, Tristan Braud, Aaron Ding, Sasu Tarkoma, and Pan Hui, for their hard work in preparing the special issue. In particular, I would like to express my gratitude to Pengyuan Zhou, who coordinated the process efficiently as lead guest editor. The guest editors have made a careful selection of five articles that address different technologies for the convergence of the metaverse and connected and automated mobility, including perception and mobile crowdsensing, digital twins, immersive applications, artificial intelligence-based edge networking, and generative pretrained transformers.
In addition to the special issue, the December issue also includes five open-call articles. The article “Federated Learning-Assisted Vehicular Edge Computing: Architecture and Research Directions,” by Zhang et al. [A1], discusses the potential of combining federated learning (FL) and mobile edge computing (MEC) to support future connected and automated vehicles (CAVs). MEC provides vehicles with convenient and on-demand access to edge servers in proximity with enhanced computing and storage resources so that CAVs can offload computationally intensive and delay-sensitive applications to the network edge. Many of these applications will require machine learning (ML) methods for processing large amounts of data. Combining FL with MEC allows vehicles to train locally the ML models, keep their original data, and share only local models to the edge servers. The article reviews the application of FL in vehicular networks and introduces a general architecture to combine FL and MEC to support CAVs. The article analyzes the impact of high mobility on the operation of FL solutions combined with MEC and proposes a mobility- and data-aware method to select the vehicles participating in the FL learning process. The analysis shows that an intelligent selection of the vehicles improves the FL learning process and reduces the latency. The article concludes with recommendations for designing FL-assisted MEC systems and future research.
The article “Enhancement of Satellite-to-Phone Link Budget : An Approach Using Distributed Beamforming,” by Xu et al. [A2], presents a beamforming solution to improve the link budget of low-Earth orbit (LEO) satellite connectivity on cell phones. Standard cell phones generally do not have enough reception gain, and a LEO satellite’s transmit power and antenna gain are limited by size and weight. This prevents direct communication between LEO satellites and user equipment due to an insufficient link budget, and it generally requires a ground device to forward the satellite signal to the user equipment. The authors propose a distributed beamforming solution that can compensate for the insufficient link budget and improve the budget by 6 to 12 dB when combining two or four radiation sources. This approach opens the door for possible direct network communication between LEO satellites and user equipment without having to rely on ground devices.
In “Aerial Base Stations for Global Connectivity: Is It a Feasible and Reliable Solution?” [A3], Matracia et al. discuss challenges and solutions to bridge the urban-rural digital divide and improve cellular connectivity in rural underserved areas through the use of aerial base stations (ABS). ABSs consist of unmanned aerial vehicles carrying cellular base station equipment. The article discusses the challenges of rural connectivity and compares conventional terrestrial networks with aerial networks from a technoeconomic point of view. The article reviews the impact of topological aspects of rural environments on the design of cellular networks, and it analyzes the coverage probability and reliability of communication links with ABSs. The authors conclude that efficient integration and deployment of ABSs and terrestrial base stations can be a viable technoeconomical solution to help address the urban-rural digital divide, even with a low density of ABSs.
Lee et al. analyze in their article “Wireless Powered Interference Networks: Applications, Approaches, and Challenges” [A4] the potential of wireless-powered interference networks (WPINs) to augment transmission rates and energy harvesting. WPINs build from the capabilities of wireless energy harvesting technologies to convert interference into a feasible energy source for low-powered Internet of Things devices. The authors introduce the capabilities of WPINs to make efficient use of complex cochannel interference under various topologies in future wireless networks, and they present a simultaneous wireless information and power transfer (SWIPT)-then-wireless information transfer (WIT) protocol to manage interference for bidirectional communications in WPINs through the use of SWIPT in the downlink and WIT in the uplink. The protocol is utilized to design coordinated resource management and beamforming schemes, and the authors show that the performance of WPINs can be significantly improved if the interference is adaptively controlled to increase the energy harvested while reducing the adverse effect on information decoding. The authors finally discuss research challenges and approaches for introducing advanced capabilities of WPINs.
The article “Inductive Power Transfer in Electric Vehicles: Past and Future Trends,” by Marques et al. [A5], analyzes the potential of inductive power transfer (IPT) technology to address some of the challenges of electric vehicles (EVs), including limited autonomy and range. IPT is a near-field technology that transfers power using a transmitter coil that generates a variable magnetic field, which induces a voltage across the receiver coil. The article discusses the main past and recent research topics and trends in IPT systems applied to EV technology. The main current areas of research include challenges imposed by dynamic operation mode or leakage flux control techniques, among others.
I hope that you enjoy reading this issue, and please don’t hesitate to get in touch if you have any feedback or suggestions.
[A1] X. Zhang, J. Liu, T. Hu, Z. Chang, Y. Zhang, and G. Min, “Federated learning-assisted vehicular edge computing: Architecture and research directions,” IEEE Veh. Technol. Mag., vol. 18, no. 4, pp. 75–84, Dec. 2023, doi: 10.1109/MVT.2023.3297793.
[A2] Z. Xu, Y. Gao, G. Chen, R. Fernandez, V. Basavarajappa, and R. Tafazolli, “Enhancement of satellite-to-phone link budget: An approach using distributed beamforming,” IEEE Veh. Technol. Mag., vol. 18, no. 4, pp. 85–93, Dec. 2023, doi: 10.1109/MVT.2023.3320403.
[A3] M. Matracia, M. A. Kishk, and M.-S. Alouini, “Aerial base stations for global connectivity: Is it a feasible and reliable solution?” IEEE Veh. Technol. Mag., vol. 18, no. 4, pp. 94–101, Dec. 2023, doi: 10.1109/MVT.2023.3301228.
[A4] K. Lee, H.-H. Choi, W. Lee, and V. C. M. Leung, “Wireless powered interference networks: Applications, approaches, and challenges,” IEEE Veh. Technol. Mag., vol. 18, no. 4, pp. 102–110, Dec. 2023, doi: 10.1109/MVT.2023.3306552.
[A5] E. G. Marques, V. S. Costa, A. M. S. Mendes, and M. S. Perdigão, “Inductive power transfer in electric vehicles: Past and future trends,” IEEE Veh. Technol. Mag., vol. 18, no. 4, pp. 111–122, Dec. 2023, doi: 10.1109/MVT.2023.3318840.
Digital Object Identifier 10.1109/MVT.2023.3338494