How can the integration of AI in RAN help CSPs enhance network performance?
The integration of artificial intelligence (AI) in radio access networks (RAN) is set to transform network operations, driving enhanced performance, streamlined processes, and cost-effective deployment of advanced services like 5G. This forward-looking approach to AI adoption in RAN promises to elevate the capabilities of CSPs and set new standards for operational excellence.
Main benefits of using AI in networks
Enhanced throughput
AI is used to predict and adjust radio link configurations based on channel conditions, traffic patterns, and user demands, ensuring high data rates for users with high bandwidth needs.
Improved handover speed and reduced dropped calls
AI anticipates the best target for handover and enables seamless call transfer between cells, minimizing disruptions and dropped calls caused by poor coverage, user movement, and network congestion.
Increased energy efficiency
AI predicts traffic patterns and cell usage to optimize energy consumption without compromising performance by activating or deactivating multiple-input, multiple-output (MIMO) functionalities in cells.
Network anomaly detection
AI continuously analyses network behaviour to identify unusual patterns, such as sleeping cells, allowing for early detection and corrective actions to maintain optimal network performance.
