Ooredoo Qatar: AI Digital Twin Transforms 5G RAN Optimization

The Challenge

Ooredoo Qatar, Qatar's leading telecom operator, grappled with the inefficiencies of manual Radio Access Network (RAN) optimization and troubleshooting. As 5G rollout accelerated, traditional methods proved time-consuming and unscalable [1], struggling to handle surging data demands, ensure seamless connectivity, and maintain high-quality user experiences amid complex network dynamics [2].

Performance issues like dropped calls, variable data speeds, and suboptimal resource allocation required constant human intervention, driving up operating expenses (OpEx) and delaying resolutions. With Qatar's National Digital Transformation agenda pushing for advanced 5G capabilities, Ooredoo needed a proactive, intelligent approach to RAN management without compromising network reliability [3].

Quantitative Results

• 15% reduction in radio power consumption (Energy Saver PoC)
• Proactive RAN optimization reducing troubleshooting time
• Maintained high user experience during power savings
• Reduced operating expenses via automated resolutions
• Enhanced 5G subscriber experience with seamless connectivity
• 10% spectral efficiency gains (Ericsson AI RAN benchmarks)

Implementation Details

Partnership and Initial Trial Phase

In April 2022, Ooredoo Qatar initiated a trial of Ericsson Performance Optimizers, a suite of AI-powered applications designed to analyze the RAN and deliver optimization insights. This marked the starting point for integrating advanced AI into their 5G network operations.[2] The trial focused on identifying inefficiencies in real-world scenarios, setting the stage for broader deployment.

Full Deployment on Microsoft Azure (2023)

By early 2023, Ooredoo and Ericsson successfully deployed cloud-native cognitive software atop Microsoft's sovereign cloud datacenter in Qatar. The core innovation is the digital twin technology, which mirrors the live RAN, allowing safe simulations of configurations. Coupled with deep reinforcement learning, the system learns from network data to proactively recommend optimizations and resolve issues like coverage gaps or interference.[1][3] This setup ensures low-latency processing, scalability for growing 5G traffic, and compliance with local data sovereignty.

Technology Integration and AI Workflow

The implementation involved integrating the AI stack with Ooredoo's existing RAN elements, including Ericsson's 5G Radio Access Network hardware. Data from network counters, KPIs, and user plane metrics feeds into the digital twin model. Machine learning algorithms, particularly DRL agents, iteratively train on this data to predict optimal parameters such as antenna tilts, power levels, and beamforming. The system operates in a closed-loop fashion: detect anomalies, simulate fixes in the twin, validate, and apply to live network.[6] Cloud deployment on Azure provided elastic compute resources, enabling rapid scaling during peak loads.

Recent Expansions and PoCs (2025)

Building on success, Ooredoo expanded with Ericsson Mediation for enhanced 5G and cloud-native capabilities.[4] A key 2025 Proof-of-Concept (PoC) for Automated Energy Saver demonstrated the AI's versatility, achieving rapid power reductions. This involved AI-driven dormant mode activations and parameter tweaks, integrated with the core optimization engine. The phased rollout—trial, deployment, PoC—minimized risks, with continuous monitoring ensuring zero service disruptions.

Overcoming Challenges in Rollout

Initial hurdles included data integration from legacy systems and ensuring AI model accuracy in Qatar's unique urban/rural topology. Ericsson's expertise addressed this via customized training datasets and hybrid on-prem/cloud models. Operator training and governance frameworks were established for AI oversight, aligning with regulatory standards. The result: a production-ready system processing terabytes of RAN data daily for real-time insights.