5G Network Traffic Generation via HMM & KDE

This project focuses on simulating 5G network traffic features to mitigate the lack of public 5G datasets. By analyzing real-world distributions of IPT and Packet Length using KDE and HMM, the model generates high-fidelity synthetic sequences. Additionally, it utilizes state-specific probability distributions to determine the Protocol Type and Traffic Direction (Upload/Download) for each packet, ensuring realistic traffic behavior.