This paper focuses on ultra-reliable low-latency Vehicle-to-Anything (V2X) communications able to meet the extreme requirements of high Levels of Automation (LoA) use cases. We introduce a system architecture and processing algorithms for the alignment of highly collimated V2X beams based either on millimeter-Wave (mmW) or Free-Space Optics (FSO). Beam-based V2X communications mainly suffer from blockage and pointing misalignment issues. This work focuses on the latter case, which is addressed by proposing a V2X architecture that enables a sensor-aided beam-tracking strategy to counteract the detrimental effect of vibrations and tilting dynamics. A parallel low-rate, low-latency, and reliable control link, in fact, is used to exchange data on vehicle kinematics (i.e., position and orientation) that assists the beam-pointing along the line-of-sight between V2X transceivers (i.e., the dominant multipath component for mmW, or the direct link for FSO). This link can be based on sub-6 GHz V2X communication, as in 5G frequency range 1 (FR1). Performance assessments are carried out to validate the robustness of the proposed methodology in coping with misalignment induced by vehicle dynamics. Numerical results show that highly directional mmW and/or FSO communications are promising candidates for massive data-rate vehicular communications even in high mobility scenarios.
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http://dx.doi.org/10.3390/s20123573 | DOI Listing |
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January 2025
Dept. of Neurology, University of Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
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January 2025
Key Laboratory of Urban and Architectural Heritage Conservation, Ministry of Education, School of Architecture, Southeast University, 2# Sipailou, Nanjing, 210096, China.
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January 2025
Department of Electrical and Computer Engineering, Aarhus University, Aarhus, 8200, Denmark.
Significant progress has been made through the optimization of modelling and device architecture solar cells has proven to be a valuable and highly effective approach for gaining a deeper understanding of the underlying physical processes in solar cells. Consequently, this research has conducted a two-dimensional (2D) perovskite solar cells (PSCs) simulation to develop an accurate model. The approach utilized in this study is based on the finite element method (FEM).
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January 2025
Department of Computer Engineering, Inha University, Incheon, Republic of Korea.
The most prevalent form of malignant tumors that originate in the brain are known as gliomas. In order to diagnose, treat, and identify risk factors, it is crucial to have precise and resilient segmentation of the tumors, along with an estimation of the patients' overall survival rate. Therefore, we have introduced a deep learning approach that employs a combination of MRI scans to accurately segment brain tumors and predict survival in patients with gliomas.
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January 2025
Civil and Transportation College, Beihua University, Jilin, China.
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