Federated Learning Based Decentralized Adaptive Intelligent Transmission Protocol for Privacy Preserving 6G Networks

This article likely presents a research paper exploring a novel approach to secure and efficient data transmission in 6G networks. The use of federated learning suggests a focus on privacy by enabling model training without sharing raw data. The decentralized and adaptive nature of the protocol implies robustness and the ability to optimize transmission based on network conditions. The focus on 6G indicates a forward-looking approach to address the challenges of next-generation communication.