Secure Cooperative Dual-RIS-Aided V2V Communication: An Evolutionary Transformer–GRU Framework for Secrecy Rate Maximization in Vehicular Networks

Elnaz Bashir; F. Hernando-Galego; Diego Martín; Farzaneh Shoushtari

doi:10.3390/wevj16070396

Publication record · 2025

Secure Cooperative Dual-RIS-Aided V2V Communication: An Evolutionary Transformer–GRU Framework for Secrecy Rate Maximization in Vehicular Networks

Authors: Elnaz Bashir · F. Hernando-Galego · Diego Martín · Farzaneh Shoushtari
Year: 2025
Publisher: MDPI
Journal or publication: World Electric Vehicle Journal
Google Scholar citations: 3

Journal indicators

CiteScore 2025 (Scopus)5.4

Best quartileQ1

Top 10% in any categoryNo

Positions by category

Automotive Engineering34/143 · Q1 · percentile 76

Scopus source ↗

JCR (Clarivate): Not verified: the supplied ranking file is Scopus CiteScore, not JCR.

Not identified in the supplied report on non-standard bibliometric behaviour (2017–2019).

The report is an independent analysis published in 2021; it is not an official ANECA ban or endorsement list.

Research summary

Evo-Transformer-GRU learns time-varying vehicular channels and jointly optimizes two cooperative intelligent surfaces to improve physical-layer secrecy. Simulations study secrecy rate, convergence and prediction robustness under changing eavesdropper positions.

Original description prepared for this website; consult the publication for its authoritative abstract.

DOI 10.3390/wevj16070396 ↗ · Open-access version ↗ · View Google Scholar record ↗