5G Monitoring & Analytics
Operators are looking ways to meet high expectations of the subscribers such as high throughput and low latency with lower cost. Additionally, ARPUs are decreasing every year so operators need additional revenue streams on top of mobile subscribers' monthly payments.
IoT use cases and private networks are some of the new revenue sources for operators. However, with the current 3G/4G technologies operators cannot provide these services at the expected levels and costs. Also, it is not possible to enable IoT services, private/enterprise networks and use cases with the existing 3G/4G networks. To overcome these challenges operators are transforming their radio and core networks to 5G technologies since 5G promises delivering higher multi-Gbps peak data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to more users.
Network slicing is one of the biggest advancements introduced with 5G. With network slicing it is possible to provide different levels of service quality to different slices that are assigned to locations, enterprises, MVNOs, etc. Monitoring and assuring high level quality of 5G networks and services are crucial to guarantee the provisioning and delivery of 5G services. For example, in network slicing service, each slice has different performance demands. To be able to provide the service at the demanded level, operators need to ensure that assigned slice meets the expected quality of the service.
Ultra Reliable Low Latency Communication (URLLC) is one of the other key pillars of 5G technology. URLLC enables several use cases such as industry automation, connected cars, healthcare, etc. Time to market of URLLC services is very critical in today’s fierce competition the telco market faces. Service assurance of the URLLC service not only helps shortening time to market of URLLC service, but also enables fast resolution of the service problems and issues.
On the other hand, new 5G architecture comes with new challenges that should be managed wisely. With 5G, radio and core network architecture radically change. All core networks are virtualized and network-based architectures are transformed to service-based architectures. Network elements which runs on dedicated physical servers are transformed to virtual network functions which run on NFV and cloud native platforms.
In short, 5G promises increased bandwidth, high speed and low latency. However, for obtaining the maximum benefit from the 5G technology, operators need to make proactive maintenance of their networks.
Argela 5G Monitoring and Analytics solution, which comprises Probes and Analytics software as virtual network functions, allows the operators to monitor 5G network interfaces between network functions. It additionally monitors 5G service functions, such as network slicing, in an end-to-end manner.
Operators using Argela’s 5G Monitoring and Analytics solution are equipped with tools to track quality metrics of 5G services, problem/event identification and troubleshooting tools to analyze and resolve network issues. It also provides means to track the key performance metrics of URLLC services and troubleshooting tools to identify and resolve URLLC service issues and problems on time.
With predictive analysis capability provided by Argela solution, it is possible to anticipate failures before they occur. AI and ML technologies are leveraged while developing these features.
One of the main architectural features of 5G network is Data control plane and User Plane seperation which is called CUPS. Argela solution is currently CUPS ready and allows monitoring and processing user plane data traffic where the control plane SWG-C, PGW-C and SGW-U, PGW-U are installed in different geographic locations. Therefore, Argela 5G Monitoring and Analytics Solution is ready to monitor 5G user plane traffic where control plane is processed by SMF and user plane is processed by UPF.
Last but not the least, it is important for operators to identify and analyze the customer experience and behavior. In order to provide high quality of experience for each subscriber and identify the next best action to be taken in case of service failure experienced by a subscriber, Argela provides Customer Experience Index and Next Best Action tools utilizing Machine Learning /Deep Learning technologies.
Virtualization and Argela vProbe
