Explore best practices we see delivering results with leading operators worldwide, structured into a practical, operator-focused framework for modern RAN Planning.
Foreword: Why future-proof RAN planning matters now | 2 |
Introduction: The evolution of RAN planning in the 5G era | 4 |
Building Block 1: AI-driven accuracy in RAN planning | 5 |
From static equations to learning models | 5 |
Key architectural elements of AI-driven accuracy | 6 |
What AI-driven accuracy enables in practice | 6 |
Building Block 2: Advanced propagation models | 7 |
Why the propagation architecture must evolve | 7 |
Elements of an advanced propagation framework | 8 |
The shift to pre-calibrated propagation models 9 and curated geodata as-a-service | 9 |
Building Block 3: Streamlined and intuitive processes 11 in RAN planning | 11 |
From siloed expert-only workflows to planning-as-a-service | 11 |
Cloud-native planning as an enabler of process modernization | 11 |
The business case for a modern planning approach | 13 |
Geodata – when you need it, where you need it | 13 |
Propagation – pre-configured for accuracy | 13 |
IT overheads – cloud collaboration and scale | 13 |
Support and maintenance – SaaS efficiencies | 14 |
RAN planning best practice – 10 key KPIs | 15 |
Conclusion: A roadmap to future-proof RAN planning | 16 |
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