Source Themes

It is challenging to meet the bandwidth and latency requirements of interactive real-time applications (e.g., virtual reality, cloud gaming, etc.) on time-varying 5G cellular links. Today’s feedback-based congestion controllers try to match the sending rate at the endhost with the estimated network capacity.

Federated learning provides the ability to learn over heterogeneous user data in a distributed manner while preserving user privacy. However, its current clients selection technique is a source of bias as it discriminates against slow clients.

RadioSaber focuses on 5G RAN slicing, where the 5G radio resources must be divided across slices (or enterprises) so as to achieve high spectrum efficiency, fairness and isolation across slices, and the ability for each slice to customize how the radio resources are divided across its own users.