I am new to machine learning and need some guidance on how to develop and connect a python-based deep neural network to a network simulator. I am using NetSim. What data from the simulator should I use? What kind of ML applications are possible?
This is how I would think of connecting a DNN to NetSim 5G and training it:
- Install necessary software and libraries. Either Julia or Python libraries.
- Create a simulation scenario in NetSim 5G.
- Use DNN to process simulation data and learn from it.
- Adjust DNN weights and biases to improve performance during training.
- Use trained DNN to make predictions or perform tasks based on simulation data.
DNNs can be connected to NetSim 5G for various applications, including network optimization, traffic prediction, fault detection, QoS prediction, and network planning. The specific use case depends on your research or project goals.
Connecting and training a DNN with NetSim 5G looks complex to me. Can consider writing to NetSim tech support for guidance.
This may be a useful paper. Discusses using RNNs and CNNs in an experimental set-up with NetSim.Conference Paper Intelligent QoS Agent Design for QoS Monitoring and Provisio...
You could look at this whitepaper https://www.tetcos.com/pdf/v13.3/Deep_Neural_Network_Model_for_5G_SINR_prediction.pdf
- Badges
- Science topic
- Similar topics
- Filing