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Intelligent Reflecting Surface Aided Vehicular Edge Computing

  • Mohammed Laroui
  • , Hassine Moungla
  • , Hossam Afifi
  • , Mohamed Y. Selim
  • , Ahmed E. Kamal
  • Djillali Liabes University
  • Université de Paris
  • Telecom Sudparis
  • Iowa State University

Research output: Contribution to journalConference articlepeer-review

Abstract

Due to the rapid increase of connected devices and network traffic, the data transport from end-user devices to destination (connected device, cloud, edge servers, etc) can be interrupted because of obstacles and problems. In this paper, we propose to integrate edge servers with the intelligent reflecting surface (IRS) in a vehicular edge computing (VEC) environment. The IRS is deployed in fixed places inside the city (fixed IRS-Edge Nodes) and in taxis and buses (mobile IRS-Edge Nodes), where it is used for both reflecting signals and executing the different client vehicles' tasks. We propose an Optimal IRS-Edge Selection (OIES) model to select the optimal IRS-Edge Node(s) that satisfy the client vehicles' requirements. Moreover, we propose an Efficient IRS-Edge Selection (EIES) algorithm to deal with the high number of client vehicles in dense networks. The numerical results demonstrate the efficiency and the feasibility of the proposed solution.

Original languageEnglish
Pages (from-to)5577-5582
Number of pages6
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
DOIs
Publication statusPublished - 1 Jan 2022
Event2022 IEEE Global Communications Conference, GLOBECOM 2022 - Rio de Janeiro, Brazil
Duration: 4 Dec 20228 Dec 2022

Keywords

  • Edge computing
  • Intelligent reflecting surfaces
  • Mobile edge computing

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