Infrastructure-Wide and Intent-Based Networking Dataset for 5G-and-beyond AI-Driven Autonomous Networks

Area of Science:

• Computer Science
• Telecommunications Engineering

Background:

• Artificial intelligence (AI) is crucial for Autonomous Networks (ANs), particularly in 5G and future cellular generations.
• High-quality networking datasets are essential for data-driven algorithms in network management and optimization.

Purpose of the Study:

• To propose the IW-IB-5GNET dataset for research and development of network management and optimization solutions.
• To support the creation of AI algorithms for informed decision-making and efficient resource optimization in 5G+ networks.

Main Methods:

• Generated an infrastructure-wide and intent-based dataset named IW-IB-5GNET.
• Utilized an emulated 5G network environment with extensive network sensor deployment for data collection.

Main Results:

• The IW-IB-5GNET dataset encompasses information across all 5G network layers.
• The dataset is built upon predefined user intents, reflecting real-world network demands.

Conclusions:

• The IW-IB-5GNET dataset is a valuable resource for advancing autonomous and intelligent network management.
• It facilitates the development of solutions that enhance overall network performance and optimization in 5G and beyond.