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Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications [Project Summary]

CITE Title : Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications [Project Summary] Creator(s) : Molisch, Andreas F Corporate Creator(s) : University of Southern California;Pacific Southwest Region 9 UTC, University of Southern California;METRANS Transportation Center (Calif.); Corporate Contributor(s) : California Department of Transportation;United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology;United States. Department of Transportation. University Transportation Centers (UTC) Program; Published Date : 2024-05-31 Report Number : PSR-22-10 TO 065 URL : /view/dot/77400 "Deep-Learning-Based Radio Channel Prediction" (2024). "Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications [Project Summary]" (2024) "Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications [Project Summary]" , 2024 Export RIS Citation Information.

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Molisch, Andreas F

2024-05-31

:

Driver-assistance systems are essential to reduce accidents and improve energy efficiency through efficient convoying. To improve their effectiveness,...
Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications

CITE Title : Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications Creator(s) : Molisch, Andreas F;Chu, Lei; Corporate Creator(s) : University of Southern California;METRANS Transportation Center (Calif.);Pacific Southwest Region 9 UTC, University of Southern California; Corporate Contributor(s) : United States. Department of Transportation. University Transportation Centers (UTC) Program;United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology;California Department of Transportation; Published Date : 2024-06-15 Report Number : 22-10 TO 065 DOI : https://doi.org/10.25554/8ed4-fw73 "Deep-Learning-Based Radio Channel Prediction" (2024). https://doi.org/10.25554/8ed4-fw73 "Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications" (2024), https://doi.org/10.25554/8ed4-fw73 "Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications" , 2024, https://doi.org/10.25554/8ed4-fw73 Export RIS Citation Information.

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Molisch, Andreas F ;

Chu, Lei

2024-06-15

:

Reliable and efficient V2V communications are essential for driver-assistance systems to reduce accidents and improve energy efficiency through effici...