Intelligent Reflecting Surface Aided Vehicular Edge Computing

• Published in: GLOBECOM 2022 - 2022 IEEE Global Communications Conference pp. 5577 - 5582
• Main Authors: Laroui, Mohammed, Moungla, Hassine, Afifi, Hossam, Selim, Mohamed Y., Kamal, Ahmed E.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04-12-2022
• Subjects: Approximation algorithms; Computational modeling; Edge computing; Global communication; Intelligent reflecting surfaces; Mobile edge computing; Numerical models; Servers; Telecommunication traffic; Urban areas
• DOI: 10.1109/GLOBECOM48099.2022.10000899

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.