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https://github.com/paulchen2713/v2x-ra-drl

Attempt to reimplement the VTC2023-Spring 'Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications' paper
https://github.com/paulchen2713/v2x-ra-drl

deep-q-networks reinforcement-learning resource-allocation v2x-communication

Last synced: about 1 month ago
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Attempt to reimplement the VTC2023-Spring 'Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications' paper

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README

        

# **V2X-RA-DRL**
Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications

## **Note**
- This is a recent upload of a project from 16 months ago. The code is somewhat poorly written, lacking in extensibility and likely not maintainable.
- It fails to pass some static analysis and has shown to have 2 potential bugs.
- The original PC that I ran the code on is dead now. I know this sounds dramatic, but shit happens sometimes. So, if the dependency doesn't work, well, there's basically nothing I can do to help.

## **Reference**
- Y. -C. Chung, H. -Y. Chang, R. Y. Chang and W. -H. Chung, "[Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications](https://ieeexplore.ieee.org/document/10200293)," *2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)*, Florence, Italy, 2023, pp. 1-7.

- If you find this code helpful, we highly recommend that you read and cite this paper.
```!
@inproceedings{chung2023deep,
title={Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications},
author={Chung, Yi-Ching and Chang, Hsin-Yuan and Chang, Ronald Y and Chung, Wei-Ho},
booktitle={2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)},
pages={1--7},
year={2023},
organization={IEEE}
}
```
```!
@INPROCEEDINGS{10200293,
author={Chung, Yi-Ching and Chang, Hsin-Yuan and Chang, Ronald Y. and Chung, Wei-Ho},
booktitle={2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)},
title={Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications},
year={2023},
volume={},
number={},
pages={1-7},
keywords={Deep learning;Vehicular and wireless technologies;Simulation;Vehicle-to-infrastructure;Vehicular ad hoc networks;Reinforcement learning;Resource management;Vehicle-to-everything (V2X) communication;deep reinforcement learning (DRL);resource allocation},
doi={10.1109/VTC2023-Spring57618.2023.10200293}}
```