5G Network Slicing Simulation project designed to explore dynamic resource allocation and performance optimization across network slices, including eMBB, mMTC, and URLLC. Developed with modular Python architecture and detailed performance metrics.

Dynamic Network Slices Allocation for 5G Networks Using RYU Controller

5G Full Dynamic Network Slice Orchestration

AI-driven 5G orchestration framework integrating dynamic network slicing (eMBB, URLLC, mMTC) with Mobile Edge Computing (MEC) for QoS-aware resource allocation and intelligent task offloading across device, edge, and cloud.

A Java implementation of dynamic bandwidth allocation for 5G network slices.

Reinforcement learning–based framework for dynamic 5G RAN network slicing. A PPO agent allocates radio resource blocks across eMBB, URLLC, and mMTC slices using SLA-aware rewards, evaluated via throughput, latency, queue stability, and SLA violation metrics.

Dynamic 5G slicing — Open5GS + Python orchestrator

5G-NSSF in free5gc orchestrates network slicing, dynamically selecting the optimal network slice for each service request.

This project demonstrates dynamic network slicing for enhanced Wi-Fi performance in 5G networks. It explores techniques to improve resource allocation and network efficiency by simulating and analyzing network slicing in real-time.

project uses a Random Forest regression model to predict dynamic RB allocation for 5G network slices (URLLC, eMBB, mMTC) based on user load and SNR conditions. The model is trained on historical data, performs feature engineering, and simulates real-time RB allocation with constraint-based post-processing to ensure valid allocations.

This project simulates dynamic 5G network slicing using Kali Linux and VMware to intelligently manage eMBB, URLLC, and mMTC resources.

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5G-Empower Runtime with a new Dynamic QoS Slicing Application.

Code and data

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This project demonstrates dynamic network slicing for enhanced Wi-Fi performance in 5G networks. It explores techniques to improve resource allocation and network efficiency by simulating and analyzing network slicing in real-time.

Intelligent 5G network platform deployed on Kubernetes with AI-powered prediction to dynamically optimize network slicing and enhance user Quality of Experience in real-time.