Project
Enhancing Network Coverage with AI RAN Automation
Challenge
Telecom operators face increasing challenges in maintaining consistent network quality as data traffic continues to grow, while the frequency bandwidth remains unchanged. Variations in signal quality parameters such as CQI, RSRQ, and SINR at the cluster level can negatively affect customer experience and potentially impact revenue. A comprehensive solution is required that can enhance coverage availability, ensure signal stability, optimize spectral efficiency, and support payload growth without performance degradation.
Solution
In collaboration with Qualcomm, Lintas Teknologi introduced Coverage Shaping Solutions powered by AI RAN Automation. This solution enables operators to automatically optimize network parameters at the cluster level, ensuring consistent signal quality while improving spectral efficiency.
By leveraging automation, the solution reduces the reliance on manual interventions, allowing faster, more accurate, and efficient network optimization.
Results
The deployment of AI-driven Coverage Shaping Solutions has delivered measurable improvements across key network quality indicators at the cluster level. Both spectral efficiency and channel quality showed consistent enhancement, while critical parameters such as signal stability and payload capacity were maintained without degradation.
This approach allowed the operator to sustain data traffic growth in line with comparable markets within the same region, while safeguarding both revenue and customer experience. As a result, the solution has proven effective in supporting long-term, data-driven network optimization strategies.
Benefits for Telecom Operators
By adopting AI-driven Coverage Shaping Solutions, operators can achieve:
- Improved customer experience through more consistent signal quality.
- Operational efficiency via automation, reducing dependency on manual optimization.
- Revenue protection and growth enablement, with no degradation in payload or RSRP.
- Scalability for increasing data demand, ensuring stable network performance under higher traffic loads.
- Competitive differentiation by leveraging AI to support future-ready network transformation.