Automation of RAN Planning and Optimisation with Naos: How Telecom Operators Achieve Unprecedented Efficiency Gains
Introduction
Telecom operators are under increasing pressure to optimise networks, reduce costs, and accelerate deployments. Automation of RAN planning and optimisation is emerging as a game-changer, enabling operators to replace manual workflows with scalable, cloud-native solutions.
Forsk's Naos is at the forefront of this transformation, delivering unprecedented efficiency gains in RAN planning and optimisation. In this article, we explore:
- How Naos automates RAN planning and optimisation workflows.
- Real-world use cases and efficiency gains.
- How to integrate Naos with existing OSS/BSS systems.
What is Naos?
Naos is Forsk's cloud-native platform for automating RAN planning and optimisation. Built on a microservices architecture, Naos enables operators to:
- Automate repetitive tasks (e.g., coverage prediction, site provisioning).
- Scale compute resources for large-scale simulations.
- Integrate with OSS/BSS using REST APIs.
Key Features of Naos
| Feature | Business Benefit |
|---|---|
| API-First Architecture | Seamless integration with OSS and BSS platforms. |
| Scalable Compute | Run nationwide 5G coverage predictions in minutes or hours, not days. |
| Automated Workflows | Reduce manual effort by automating site provisioning, coverage calculations, and optimisation workflows. |
| Cloud-Native | Deploy on AWS, Azure, or Google Cloud for flexibility and scalability. |
How Naos Drives Efficiency Gains
Naos automates end-to-end RAN planning and optimisation workflows, eliminating bottlenecks and human errors. Here's how operators achieve dramatic efficiency gains:
1. Automated Coverage Prediction
- Challenge: Manual coverage prediction is time-consuming and error-prone.
- Solution: Naos automates coverage map generation using scalable cloud compute.
- Result: Nationwide 5G coverage calculated in minutes or hours (vs. days manually).
2. Site Provisioning and Decommissioning
- Challenge: Adding or removing sites requires manual configuration and validation.
- Solution: Naos automates site selection, configuration, and validation.
- Result: Significantly faster than manual processes.
3. Continuous Optimisation
- Challenge: Network issues (e.g., coverage gaps, interference) require manual intervention and iterative optimisation.
- Solution: Naos automates parameter adjustments (e.g., tilt, PCI) based on network data to optimise performance.
- Result: Automated continuous optimisation with minimal human input.
Real-World Use Cases of Naos
Operators worldwide are using Naos to automate RAN planning and optimisation workflows. Here are some real-world examples:
Case Study 1: Nationwide 5G Coverage Prediction
- Operator: Large North American telecom provider.
- Challenge: Manual coverage prediction for 70,000+ 5G sites took weeks.
- Solution: Naos automated coverage map generation using AWS cloud compute.
- Result: Nationwide 5G coverage calculated in minutes or hours.
Case Study 2: Automated Site Decommissioning
- Operator: European telecom operator.
- Challenge: Decommissioning legacy 3G sites required manual validation.
- Solution: Naos automated site selection and validation.
- Result: Significant reduction in manual effort.
How to Integrate Naos with Existing Systems
Naos is designed for seamless integration with OSS and BSS platforms. Here's how to get started:
- API-First Integration
- Naos provides REST APIs for data exchange and automation.
- Example use cases:
- Pull network data from OSS/BSS to create an up-to-date digital twin.
- Generate coverage results and produce statistics for network planning and optimisation.
- Cloud Deployment Options
- Public cloud: Deploy Naos on AWS, Azure, or Google Cloud.
- Private cloud: Use Kubernetes for on-premises deployment.
The Future of Automation in RAN Planning and Optimisation is Here
Naos is transforming RAN planning by automating workflows, reducing costs, and accelerating deployments. Operators using Naos achieve unprecedented efficiency gains, enabling them to future-proof their networks for 5G, IoT, and beyond.
