Federated Learning for Secure and Efficient Vehicular Communications in Open RAN
Muhammad Asad,
Saima Shaukat,
Jin Nakazato
et al.
Abstract:This paper presents a comprehensive exploration of federated learning applied to vehicular communications within the context of Open RAN. Through an in-depth review of existing literature and analysis of fundamental concepts, critical challenges are identified within the current methodologies employed in this sphere. A novel framework is proposed to address these shortcomings, fundamentally based on federated learning principles. This framework aims to enhance security and efficiency in vehicular communication… Show more
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