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5G Monetization Depends On Telco Cloud Success

Forbes Technology Council

Ben Parker is Chief Technology Officer at Guavus, a Thales company and pioneer in telecom AI-driven analytics. 

Most of the world's telecom operators have committed to rolling out 5G, but the buildouts won't come cheap. Accenture Strategy estimates that U.S. operators alone will spend as much as $275 billion over seven years in 5G core networks and cell sites. As a telco CFO or CIO, how do you control costs and best monetize the network to justify and quickly recoup your 5G investments?

5G buildout justifications are based largely on new — and often real-time — use cases that assume extreme sophistication in mobile networks. However, making those use cases a reality requires operators to find an affordable way to rapidly scale their infrastructures to deliver distributed resources wherever they're needed. That means embracing the concept of telco clouds.

While there's been talk of telco clouds for years, they haven't progressed much beyond network functions virtualization (NFV). NFV deployments have suffered from a lack of "cloud-native" components, as operators tend to use NFV to quickly spin up a new service here and there but haven't invested in bona fide multicloud service delivery platforms — and the associated operational processes and people skills — needed to fully address both current and future deployment requirements.

So how to get over the hump? From the work we've done with 5G operators, I've learned that when telcos strike partnerships with cloud providers and integrate their ecosystems for reach, scalability and unified analytics, they can start seeing the 5G returns they expect.

Adopting The OpEx Model.

Like enterprises before them, many operators will soon find themselves moving away from CapEx-centric models of network operation and embracing the OpEx model afforded by cloud services. They may deploy traditional public clouds and adopt managed cloud services, whereby providers such as Amazon, Microsoft and Google move their infrastructure into telco data centers.

Telco partnerships with large cloud providers could be just the ticket for merging infrastructures in ways that make 5G more affordable and able to turn a profit faster. Such partnerships could also create all-new business models for jointly delivering innovative, customer-centric services based on analytics derived by merging both types of organizations' customer databases.

Specifically, cloud economics and partnerships could help operators achieve the following business outcomes:

• Monetize 5G as a business services platform.

• Engage customers in new ways with data-driven experiences.

• Improve operational efficiency across telecom core systems.

Operators will have to transition legacy service platforms into cloud-native platforms to partner with cloud providers. Many have been using NFV to virtualize and automate portions of their infrastructures, but NFV is just the jumping-off point to migrating to fully cloud-native infrastructures for service innovation.

Role Of Network Slicing And NWDAF.

The Third-Generation Partnership Project (3GPP) specifies a 5G standard called "network slicing," which creates many virtual, isolated end-to-end network segments across the physical network infrastructure. Network slicing enables new business opportunities for services that require connectivity with very different characteristics. Using it, operators can divide and grow the network on an as-a-service and on-demand basis to accommodate diverse requirements requested by individual applications and services at scale. A few examples include:

• High-throughput apps such as streaming video and gaming.

• Ultra-reliable low-latency communication for sensors in autonomous cars.

• Massive IoT connections.

One enterprise customer could use one network slice for all of its transmissions or multiple network slices to serve the different application and service requirements mentioned.

Another 3GPP standard is network data analytics function (NWDAF). NWDAF monitors all aspects of each network "slice" for compliance with relevant service-level agreements. Operators can make use of NWDAF in their infrastructures to help control service levels and deliver strong customer experiences.

IoT, Edge Computing And AI/ML-Based Analytics

Real-time, data-intensive 5G applications will require mobile edge computing infrastructure. This "services edge" comprises small data centers peppered throughout the radio-access network, which sits between a customer's CPE or mobile device and the provider's network aggregation infrastructure. The edge data center could be owned by the mobile operator, a cloud partner of the operator or both entities. Data processing close to the source reduces end-to-end applications latency for the real-time emerging applications and lowers the volume of data traversing the network backbone to the cloud.

Cloud is a key element of the modernization of telecom networks and services. As operator networks grow more software-based, telcos using the cloud should increasingly adopt machine learning (ML), artificial intelligence (AI) and data analytics to further improve their operations.

Virtualization and cloudification allow for unprecedented levels of network automation, which is growing in importance as mobile workloads become increasingly dynamic. With increasing numbers of applications, there's little or no time for human interactions. And without a service- and customer-centric network view, operators can't understand the customer experience sufficiently to focus resources where and when needed.

With real-time inventory, analytics and AI-based machine learning, however, self-learning networks combine with human expertise to augment and automate operations, predict issues, scale knowledge and provide consistent problem resolution. They can also predict traffic loads and network conditions to enable automatic, optimal provisioning of network resources to improve service levels.

When evaluating AI-based analytics solutions to help you monetize your 5G network, consider the following:

• Consider how your operations teams will need to adapt to 5G. Having more cell sites, small cells, in-building deployment and virtual network elements in addition to new network functions such as multiaccess edge compute will put pressure on traditional operations teams. AI/ML-based analytics can help you reduce this noise and complexity and improve customer service.

• Because 5G will launch a new portfolio of enterprise services, ensure your AI/ML analytics solution has the capabilities to help you predict and prioritize many service degradations before the customer sees truly degraded performance or complete outages.

• Ensure your AI/ML analytics solution provider is cloud-native and can support private cloud deployments and public cloud deployments seamlessly. Cloud lock-in carries the same risks that vendor lock-in did in the past. Ensure your tools do not facilitate this lock-in.

• In your AI/ML analytics integration with 5G, focus on technologies outlined in the NWDAF standard being defined by 3GPP (the standards development body for mobile networks) as well as functions beyond what the standard envisions. Ensure your analytics solution can support these.

The Way Forward

To thrive in a 5G world, I believe operators must exploit virtualization and embrace cloud economics to overcome immense buildout costs and navigate new revenue streams without undue complexity. Many operators have been attempting to reinvent themselves for some time, with varying levels of success. However, the arrival of the 5G era may finally be the impetus they need to at last embrace wholesale change.

Partnerships with cloud providers for edge infrastructure, adoption of cloud-native and virtualization technologies and embracing AI-enabled, automated network operations and customer analytics are all in the near-term cards for telcos. Without these tools, operators will be hard-pressed to harness the limitless business potential of 5G when network cost and complexity challenges rear their heads.


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