NextG wireless will heavily rely on Federated Learning (FL) applications to learn context-aware AI solutions from the massive amount of generated data. Ensuring the reliability of wireless links for such applications is paramount, especially for FL where packet loss can severely hamper performance and efficiency. Traditional approaches fall short under the high packet loss characteristics of wireless networks. This demo shows how the integration of Fountain Codes (FC) into the FL process can bring notable improvements in packet transmission efficiency, especially under high packet loss conditions.
Enabling Lightweight Federated Learning in NextG Wireless Networks
Andriolli, Nicola;
2024-01-01
Abstract
NextG wireless will heavily rely on Federated Learning (FL) applications to learn context-aware AI solutions from the massive amount of generated data. Ensuring the reliability of wireless links for such applications is paramount, especially for FL where packet loss can severely hamper performance and efficiency. Traditional approaches fall short under the high packet loss characteristics of wireless networks. This demo shows how the integration of Fountain Codes (FC) into the FL process can bring notable improvements in packet transmission efficiency, especially under high packet loss conditions.File in questo prodotto:
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