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  • 标题:The Use of Meta-Surfaces in Vehicular Networks
  • 本地全文:下载
  • 作者:Barbara M. Masini ; Cristiano M. Silva ; Ali Balador
  • 期刊名称:Journal of Sensor and Actuator Networks
  • 电子版ISSN:2224-2708
  • 出版年度:2020
  • 卷号:9
  • 期号:1
  • 页码:15-32
  • DOI:10.3390/jsan9010015
  • 出版社:MDPI Publishing
  • 摘要:Mobility as a service is becoming a new paradigm in the direction of travel planning on the basis of the best service offered by the travelled roads. Hence, the environment in which people move will become smarter and more and more connected to grant services along the whole path. This opens new challenges related not only to the on board connectivity and wireless access technologies, but also on the reliability and efficiency of the surrounding environment. In this context, reconfigurable meta-surfaces play a crucial role, since they can be used to coat buildings, vehicles or any other suitable surfaces and let the environment become an active part of the communication system by opportunistically redirecting (i.e., reflecting, without generating new waves) signals to the target receivers. The objective of this paper is to highlight the limits of current wireless access technologies for vehicular scenarios and to discuss the potential impact of a smart environment made of reconfigurable meta-surfaces on some next generation vehicular use cases, such as cooperative driving and vulnerable road users (VRUs) detection. In addition, a preliminary model is presented to derive, in a simplified way, the performance of an IEEE 802.11p network in terms of collision probability. Even if analytical and based on simplified assumptions, this model has been validated through simulations and allows to compare the performance of the network with and without reconfigurable meta-surfaces.
  • 关键词:connected vehicles; reconfigurable meta-surface; smart environment; cooperative driving; vulnerable road user detection; collision probability connected vehicles ; reconfigurable meta-surface ; smart environment ; cooperative driving ; vulnerable road user detection ; collision probability
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