Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Teleoperated vehicles over 5G face reliability issues due to reactive handovers. We propose a deep learning framework using time-series radio data to predict handover onset, target cells, and link quality. These forecasts enable proactive actions like bandwidth scaling or control rate adjustment to ensure stability.

Notifications You must be signed in to change notification settings

zende039/deepfusion_v1

Repository files navigation

deepfusion_v1

Teleoperated vehicles over 5G face reliability issues due to reactive handovers. We propose a deep learning framework using time-series radio data to predict handover onset, target cells, and link quality. These forecasts enable proactive actions like bandwidth scaling or control rate adjustment to ensure stability.

About

Teleoperated vehicles over 5G face reliability issues due to reactive handovers. We propose a deep learning framework using time-series radio data to predict handover onset, target cells, and link quality. These forecasts enable proactive actions like bandwidth scaling or control rate adjustment to ensure stability.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published