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DNN model for path loss prediction v1.1

This deep neural network model is designed to predict the path loss of Vehicle Communication, and the dataset required for model learning is obtained through the ns3-SUMO integrated simulation testbed*. DNN model use the most common Deep Neural Networks model to predict path loss. Each model is implemented in the form of a Jupiter notebook ipynb file, and CNN and LSTM versions are currently being updated. Users can change most DNN model parameters, but care must be taken when changing data fields.

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TBU

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Sangmo Sung, UNLab, [email protected]

Last update

2022.07.07

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Path loss prediction using DNN model

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