Feature articles - November 2024
Terahertz communications, electrical vehicle charging, and artificial intelligence for wireless communications are some of the popular topics for publications. In the following, let us provide you with a one-stop destination to know about the latest publications in these areas. We hope that the short summary of these feature articles written in layman language may make your reading a pleasure!
Invited paper: Investigating the WSSUS Assumption in 300 GHz Time-Variant Channels in Industrial Environments
Authors: Varvara V. Elesina; Carla E. Reinhardt; Lennart Thielecke; Tobias Doeker; Thomas Kürner
Published in volume 5, IEEE Open Journal of Vehicular Technology
IEEExplore version
Summary contributed by Thomas Kürner (Author):
The upcoming Industry 4.0 demands wireless communication systems that support extremely high data rates, stringent reliability and ultra-low latency. Terahertz (THz) frequencies offer a potential solution to meet these requirements, but industrial environments pose unique challenges due to their dynamic nature, with moving objects and complex surfaces causing significant reflection, diffraction and scattering. To achieve the performance and reliability standards of Industry 4.0, specialized channel models tailored to the highly variable conditions in industrial settings are essential. The wide-sense stationary (WSS) and uncorrelated scattering (US) assumptions are used to model time-variant channels, treating them as stationary over short time and frequency intervals, referred to as stationary time and stationary frequency. These assumptions simplify the analysis by enabling the use of models that consider constant channel properties within these intervals. Therefore, for reliable channel characterization and model development, it is crucial to determine the regions where the WSSUS assumptions hold true.
In this paper, these regions of applicability were determined for 300 GHz time-variant channels in industrial environments using Local Scattering Function (LSF) collinearity metrics in both time and frequency domains. The research involved a series of measurement campaigns, including the “Access Point” scenario, where a moving receiver communicates with a static access point, and two variations of blockage scenarios comparing different blockage objects – a metal plate and a robotic manipulator arm – as well as different speeds of the blockage objects.
Comparison and Analysis of Algorithms for Coordinated EV Charging to Reduce Power Grid Impact
Authors: Cesar Diaz-Londono; Paolo Maffezzoni; Luca Daniel; Giambattista Gruosso
Published in volume 5, IEEE Open Journal of Vehicular Technology
IEEExplore
Summary contributed by Giambattista Gruosso (Author):
The growing adoption of electric vehicles (EVs) is creating problems in integrating the EV charging infrastructure with the electricity grid. Uncoordinated charging can lead to overloading of transformers or lines, power quality problems and imbalances. This article presents two intelligent charging coordinators per group of EV charging stations, with the aim of managing charging while taking into account the power limits of transformers, as well as other economic aspects. Both coordinators address uncertainties related to the arrival time of EVs, charging status and inflexible transformer demands. Real-world data sets were used to evaluate the performance of the proposed strategies through simulation studies on different scenarios. The comparative analysis shows that the flexibility maximisation strategy effectively mitigates transformer overload events. The study emphasises the importance of innovative charging strategies for seamless integration of electric vehicles and the need for coordinated charging pools for reliable charging operations.
AI-Based Beam Management in 3GPP: Optimizing Data Collection Time Window for Temporal Beam Prediction
Authors: Yingshuang Bai; Jiawei Zhang; Chen Sun; Le Zhao; Haojin Li; Xiaoxue Wang
Published in volume 5, IEEE Open Journal of Vehicular Technology
IEEExplore
Summary contributed by Chen Sun (Author):
AI for beam management is a critical focus at the physical layer design of 3GPP release 19. To ensure quality, AI model management includes monitoring predictions against legacy results and adapting models based on user equipment (UE) location and speed. Enhancing model performance can reduce fallback to traditional methods. This study proposes adjusting the data collection window size based on UE speed to optimize AI performance for moving UEs.
About IEEE Open Journal of Vehicular Technology (OJVT)
The IEEE Open Journal of Vehicular Technology covers the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation. (a) Mobile radio shall include all terrestrial mobile services. (b) Motor vehicles shall include the components and systems and motive power for propulsion and auxiliary functions. (c) Land transportation shall include the components and systems used in both automated and non-automated facets of ground transport technology.