Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CFmMIMO

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Publication Details

Journal
SPIRE - Sciences Po Institutional REpository
Published
2025-09-22
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CFmMIMO

SPIRE - Sciences Po Institutional REpository
CRISPR and Genetic Engineering
article

Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CFmMIMO

article en

Abstract

No abstract available for this paper.
SPIRE - Sciences Po Institutional REpository
Institut national de recherche en sciences et technologies du numérique (FR), Université de Lille (FR), Laboratoire d'Automatique, de Mécanique et d'Informatique Industrielles et Humaines (FR), Centre Inria de l'Université de Lille (FR)
Région Hauts-de-France
Decent work and economic growth
Openalex Percentile: Top 50%
CRISPR and Genetic Engineering
Open Access PDFOpenAlex
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Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CFmMIMO · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS