Using standard datasets for Artificial Intelligence (AI) and Machine Learning (ML) analysis of Next Generation Radio Access Networks (RAN) will not solve many of the critical RAN capacity and coverage issues or automated intelligence goals due to their complex objectives. Legacy signaling datasets can no longer simply be correlated to resolve performance issues and service objectives for these advanced 4G/5G networks.

Communications Service Providers (CSPs) know that the only path forward to next-generation AI/ML automation intelligence framework is to apply stateful analysis of raw RAN datasets and all critical emerging network variables prior to feeding AI/ML frameworks. And this path requires a journey of discovery to analyze data at the source.

With 30+ years of experience working with data at NETSCOUT, we know data secrets and we are helping CSPs succeed with their next generation 4G/5G networks.

Join NETSCOUT’s RAN expert, Robert Froehlich, Sr. Director of Product Management, in this webinar, to learn about these four critical issues in 4G and 5G Non-Standalone (NSA) and Standalone (SA) networks:

• The impact of poorly configured neighboring cells on service and subscriber experience
• Why single call analysis is no longer viable to optimize carrier aggregation
• Why optimizing intra-cell elements for capacity is important
• Why AI/ML algorithms need network source, problem, or use case-specific datasets

The Secret is Out! We invite you to join us to discuss the details.

Request Free!