5G will soon enable operators to provide new and diverse services.
But 5G simultaneously brings new and significant challenges for network operations and service assurance.
To deploy and operate complex, scalable converged pre-5G and 5G networks, operators will need to increase efficiency, optimize performance and automate their network processes while lowering both operating and investment costs. Network automation and AI are key to achieving these goals.
This report that was sponsored by P.I. Works describes how Service Providers who become ‘5G Ready’ can leverage next generation automation and AI capabilities today and make 5G both feasible and profitable as they accelerate their digital transformation.
Table of Contents
Introduction: 5G Diverse Use Cases and Performance Demand New Approach
Complex Network Environment – Five Challenges for 5G
- Multi-Technology
- Multi-Band
- Multi-Layer
- Massive MIMO
- Multi-Architecture
Three Critical Operator Requirements Leverage Automation and AI for 5G
1. Optimize 5G Efficiency across vast numbers of cells and smart antennas as well as diverse use cases.
2. Automate performance and operations processes end-to-end (E2E).
Network Automation is Key to Operator 5G Success
3. Lower network costs.
RF Engineering Costs
Six Capabilities that create ‘5G Ready’ Networks now
- Slice Aware Optimization
- Backhaul Aware Optimization
- Smart Capacity Planning
- Predictive Energy Saving
- Automated Advanced MIMO Optimization
- Wide Area Resource Coordination will require intelligent automation
Benefits of ‘5G Ready’ Networks can enhance Operations today
Technical Benefits
Business Benefits – Lower CapEx and OpEx
Operators will see immediate Cost Reduction, faster Time to Market and accelerated Digital Transformation
Exhibits
- 5G Use Cases
- Diverse Use Cases and Performance Requirements and Expected Performance
- Site OPEX - Power now dominates Site Rental and Maintenance Costs
- Mapping between 5G Requirements and Network Automation Features
- Tier 1 European Operator (20m subs.) Backhaul Optimization Case Example
- Hourly Average Number of Active UEs, Prediction of Active UE Number in Given Sector
- Tier 1 European Operator Energy Savings Case Example
- Leveraging AI for Network Transformation – Ooredoo Group