Ensuring the business value of 5G with network analytics and insights
Communication service providers are on a transformational journey to become digital service providers (DSPs). 5G technology is regarded as an essential enabler in this transformation. Representing a giant technical leap in network capabilities, 5G will help DSPs to develop new business models in co-operation with industry verticals as diverse as automated vehicles, industrial automation, assisted living and transportation systems.
In order to successfully monetize their network platforms, DSPs must match their offerings to the needs of enterprises and vertical industry players. Beyond simple connectivity, they need to expose higher layer capabilities, such as network resource orchestration, analytics capabilities and business and operations automation. In this way, digital service providers can productize the full capabilities of their networks as digital value platforms that support new co-operative business models.
The ability to create network slices with 5G is a key technical enabler for these new business models. An important new business service will be readily configured slices for different technical and business purposes, which enterprises may in turn monetize. As virtualized instances of an entire end-to-end network, 5G slices can support specific functions, such as manufacturing automation, and can be tailored to an applications’ different bandwidth, latency, resiliency and security requirements. A slice can also provide computing and memory resources.
Network and service quality assurance will be critical to the delivery of these value-enhanced services. A key analytics tool in the network insights toolbox will be the slice ‘speedometer’. By speedometer we refer to a set of always-on tools, such as machine-learning anomaly detection and localization, that can provide actionnable insights in real-time in the dynamic 5G network environment. These analytics tools will augment operational management by network engineers and eventually support closed-loop automation.
Network analytics data and insights should support multiple applications including customer experience insights tools and business partners’ external analytics systems. The data and insights need to be provided in a format that provides the best business value for the various user groups. Insights into network performance and the associated customer experience must be available on the fly to allow for fast corrective actions and, ultimately, dynamic initiation and scaling of network resources, including slices, as part of closed-loop network assurance.
Advanced network insights and 5G analytics capabilities are essential, even in the 5G technology introduction phase, to ensure the solid technical support of emerging business opportunities. Multiple use cases can be supported throughout the 5G network deployment phases:
- When 5G networks are being planned, the first step is to assess the market for locations where 5G capabilities are in greatest demand. Network analytics can provide valuable insights on the location of high-bandwidth application users.
- When the 5G trial network has been deployed and the trial period has begun, analytics can assess the readiness of radio and core network resources to deliver services. Intelligent analytics tools can investigate, for example, the contribution of individual network elements to the end-to-end service performance, handovers within 5G and between 4G and 5G at specific locations, as well as performance per device type.
- The analytics results and insights gained during the trial period can be leveraged in the network planning phase to support the deployment of the new 5G radio network, mobile backhaul and core network resources. In addition to network resource dimensioning, the network slices and their QoS levels can also be planned.
- At final deployment, analytics can assess service quality so that optimizations can be implemented. These activities will continue over the network’s lifetime. Automated root cause analysis processes and automated network optimization with closed loops will help to improve network quality and reduce unnecessary processing load.
5G networks analytics and insights need to keep pace with evolving and diverse 5G use cases. At the extremes we have to ensure very high throughput for home and mobile broadband users, ultra-low latency for vehicular communications to support very fast mobility and handovers, and serve internet of things and industrial robotics applications that provide connectivity for a huge number of devices but with low throughput rate per device.
While we already have comprehensive offerings to analyze the customers’ experience, the increasing population of connected “things” and the evolution to the new 5G network architecture will set new requirements for real-time service-level agreement (SLA) monitoring. This calls for new capabilities in network insight tools and capabilities to provide the network and service quality assurance that will be critical to the delivery of value-enhanced 5G services to enterprises and industry verticals.
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