FEDERATED LEARNING SYSTEM AND METHOD WITH ADAPTIVE NOISE AND DIFFERENTIAL PRIVACY
Abasi, Ammar Kamal Aloqaily, Moayad Guizani, Mohsen
Abasi, Ammar Kamal
Aloqaily, Moayad
Guizani, Mohsen
Supervisor
Department
Machine Learning
Embargo End Date
Type
Patent
Date
2025
License
Language
English
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Abstract
A wireless communication network method and system that includes a central server, cellular base stations, edge computing devices, and client devices. The client devices send uplink pilot sequences, which are collected and aggregated by the base stations. The base stations then relay this aggregated pilot data to the central server. The central server deploys network weights for a global deep learning neural network model to the base stations for incorporation into respective local deep learning models, trained to predict optimal beamforming vectors, to the base stations for incorporation into respective local deep learning model. During training the central server integrates adaptive noise into weights received for each of the local deep learning models.
Citation
“FEDERATED LEARNING SYSTEM AND METHOD WITH ADAPTIVE NOISE AND DIFFERENTIAL PRIVACY - Mohamed bin Zayed University of Artificial Intelligence.” Accessed: Apr. 15, 2025. [Online]. Available: https://www.freepatentsonline.com/y2025/0119251.html
Source
US Patent App. 18/544,556, 2025
Conference
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Publisher
Justia