Security of AI-Driven Beam Selection for Distributed MIMO in an Adversarial Setting

Security of AI-Driven Beam Selection for Distributed MIMO in an Adversarial Setting

In distributed multiple-input multiple-output (D-MIMO) networks, beam selection is necessary to predict the best beam and radio units (RUs) to serve the users in an optimum way. Finding the best RU and beam requires measuring the downlink channel for all possible RU/beam pairs, which becomes a resou...

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Bibliographic Details
Main Authors: Omer Faruk Tuna, Fehmi Emre Kadan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Adversarial machine learning
beam selection
cell-free massive MIMO
deep learning
distributed MIMO
security
Online Access:https://ieeexplore.ieee.org/document/10474020/

Internet

https://ieeexplore.ieee.org/document/10474020/

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