5G rollout will open new opportunities

Operator challenges in launching 5G

5G technology has made significant progress on several fronts over the last few years. There are more 5G-compatible devices in the market like the iPhone 12 and home routers. Wireless RAN infrastructure and cloud technologies have been developed to support next-gen capabilities. And the foundation for a potentially rich business ecosystem of partnerships is also emerging. But adoption is still in the nascent stage.
Operators today have a host of concerns in transitioning their networks to 5G, which include:

• Reluctance to make the massive investment required for wide 5G coverage.
• Lack of spectrum availability in many regions and local regulatory challenges.
• Low prevalence of 5G devices, meaning operators may not be able to upsell consumers.
• Technical complications in implementing 5G alongside an existing LTE network, as it would lead to complex network infrastructure that presents difficulties in management and high maintenance costs.

How operators can swiftly launch 5G

Using a combination of mid-band and low-band spectrum

While multi-gigabit 5G speeds are seen only on high-band spectrum (mmWave), many operators have proven success in using sub-6 spectrum in low bands and mid bands for a 5G launch on a wider scale. Using a combination of spectrum in low bands and mid bands also promises larger geographical coverage with higher bandwidth. This approach will result in a balanced 5G network that is faster than 4G, ensuring the best performance indoors and outdoors.

Following a two-phase NSA approach

Technically called the eUTRA-NR Dual Connectivity (EN-DC) approach, this will allow operators to reuse and leverage their existing resources, keeping the promise of 5G intact. The 5G radio (gNodeB) can connect to the EPC (the LTE core), enabling implementation of a 5G Non-Standalone (NSA) deployment. This approach will immediately enable the enhanced mobile broadband (eMBB) use case. Voice calls will be sent over the 4G network using EPS fallback.

Issue eSIMs instead of physical SIM cards

eSIM or embedded SIM is the electronic form of a physical SIM card. eSIMs are mounted permanently to a device. A user can digitally add plans from cellular operators to their eSIM without having to physically replace the SIM card. The eSIM not only improves design flexibility, it also allows the operator to digitally distribute subscriptions in bulk. It will enable faster time-to-market for operators, as a 5G eSIM can be simply delivered in the form of a QR code via email, making it much easier to distribute than physical SIMs.

Most major operators now support eSIMs. The number of mobile devices that support them is steadily growing, and will soon be far more widespread.

Prioritize network virtualization

Arguably the best thing about 5G is its cloud-native architecture. A virtualized 5G RAN and core can reside on generic commercial off-the-shelf (COTS) hardware, eliminating dependence on proprietary hardware vendors. This approach is much more flexible and cost-efficient as it will allow operators to scale up hardware resources with increasing user traffic. A 4G virtualized RAN can enable 5G with only a software update. Enhancements to network functions can be delivered via software patches. Operators will benefit significantly from virtualizing their 4G networks on priority, as it will enable a hassle-free, easier, faster 5G rollout.

Begin with private 5G networks

Private 5G is a dedicated and standalone next-gen cellular network best suitable for relatively smaller and more confined areas like universities, airports, campuses, buildings, and more. This private network can be launched in a matter of weeks with a limited resource footprint. It provides higher bandwidth to enable all 5G business use cases over a secure and private connection for different Industry 4.0 applications. A specialized compact core makes the installation easier and faster.

Enabling private 5G networks for enterprise clients is the best fit for operators who want to soft launch a real-world 5G network on a smaller scale before moving forward with a more large-scale launch.

Forge partnerships to improve the device ecosystem

Even though 5G launches are rapidly progressing around the world, the device ecosystem is still limited. Though most of the mid-range smartphones launched in 2021 support 5G, many users still need to upgrade their existing devices to experience 5G. What operators can do here is partner with OEMs to offer 5G mobile phones and Mi-Fi devices at a subsidized price to drive consumer interest. Trade-in programs will also help. This will enable operators to gain major traction for a faster 5G rollout and drive competition around the market.

Conclusion

With its cloud-first architecture, high bandwidth, and low latency, 5G has been emerging as a platform that will drive innovation in various sectors like healthcare, automobiles, logistics, massive IoT, and more. Industrial IoT and mission-critical use cases will benefit from the always-on and real-time connectivity of this next-gen network.

Early 5G rollout will give operators more time and opportunities to explore new use cases. In an increasingly competitive and dynamically changing market, the first-mover advantage is key.

Alepo’s industry-leading 5G Core solutions enable swift and easy deployment, provide a low resource footprint, and ensure standards-compliant infrastructure for a scalable and future-proof network. They enable operators to generate more revenue from avenues that were previously unexplored in telecom. Partnering with leading technology partners, Alepo delivers end-to-end 5G solutions that have enabled commercial success for over a dozen real-world deployments globally.

Alepo’s 5G Core Network Architecture

To begin your next-gen journey today, email us at market.development@alepo.com.

5G analytics systems and the predictive network

Before we dive into the technical specifics, let’s first understand why predictive networks are relevant for operators.

Business benefits of predictive networks

The predictive network enables a host of benefits to service providers, including:

• Ensure Quality of Service (QoS), Quality of Experience (QoE), and Service Level Agreements (SLAs) for 5G services by intelligently tuning to network conditions
• Prevent performance issues, predicting them before they occur and taking anticipatory corrective measures
• Lower downtime by minimizing network disruptions
• Support advanced next-gen use cases
• Maximize return on network-capacity investments
• Continuously tune the network and balance network load to prevent over-engineering

Operator success will be defined by ensuring that their predictive systems can manage their networks more efficiently while ensuring a superior customer experience.

What exactly is a predictive network?

Traditionally, proactive systems, popularly known as Self-Organizing Networks (SON), have analyzed real-time network data to detect anomalies either when an event occurred, or the system was impacted. Their algorithms would then suggest a resolution or take corrective actions that involve human intervention.

In contrast, a predictive network uses months of historical data to predict the recurrence of network events. It essentially treats each event as a statistical problem that can be solved using Artificial Intelligence (AI) and Machine Learning (ML) techniques, learning from the past and predicting what it should anticipate.

The role of predictive analytics in the 5G ecosystem

5G acts as a catalyst for predictive networks because it introduces dedicated data analytics network functions (NFs). Standards bodies have defined Network Data Analytics Function (NWDAF) and Network Exposure Function (NEF) to provide a centralized predictive analytics platform for the 5G core network. These NFs collect and expose network data in real-time to machine learning applications deployed at the network edge.

3GPP has also defined standardization guidelines for data collection, predefined analytics insights, and data exposure interfaces for customers. Accordingly, the NWDAF collects data from multiple sources like user equipment, network functions, network edge, data plane, operation, administration, and maintenance (OAM) systems, and more.

The data gathered by NWDAF can be fed into an analytics engine to provide insights and take necessary actions. It is designed to defragment proprietary network analytics solutions and standardize the way mobile network data is produced and consumed.

The 5G NWDAF, combined with AI and ML, empowers proactive closed-loop network operations, ensuring the network can analyze historical data and learn from it.

The ubiquitous architecture of 5G includes an edge NWDAF co-located with core network functions and a central NWDAF. The edge NWDAF serves low and ultralow latency use cases, while the central NWDAF supports use cases that do not have real-time requirements. It also includes functions such as the data and ML models repository that help ensure the AI/ML models and continuously trained.

Along with NWDAF, 5G also introduces data analytics functions at the following layers:

• Big data, management, and orchestration (Big Data/MDAF)
• Application function level (AFDAF)
• User equipment/RAN (DAF)
• Data network (DN-DAF)

With these critical 5G functions and an edge platform, the network can meet the performance needs of more complex next-gen use cases. It will develop a system to capture network data from all functions and understand the network; measure and predict service performance; and proactively ensure high QoE, QoS, and network availability round the clock. Automating this system using AI/ML will enable operators to maximize return on investment.

Predictive analytics use cases

Some of the many use cases that can be powered by NWDAF and AI/ML include:

Analytics systems today and into the future

Key stages of a network’s analytics journey

The analytics journey can be classified into four stages:

• Context-sensitive or diagnostic analytics gathers and visualizes data, identifies patterns in historical data, and detects why the event occurred.
• Predictive analytics analyzes large volumes of data and forecasts probable future events, using machine learning techniques.
• Prescriptive analytics provides insights and options to optimize the network.
• Cognitive analytics takes optimized decisions to rectify problems without human intervention.

Broadly speaking, the industry is currently at the predictive analytics stage. With the advent of 5G analytics functions and maturity in AI/ML algorithms, we will soon see cognitive systems taking intelligent decisions without human intervention.

The future predictive network will analyze large datasets from multiple channels and identify complex network patterns, thus making near-accurate predictions. To achieve this, the operator’s monitoring and maintenance system must rely on 5G NWDAF and advanced predictive algorithms, both of which have equally innovative core functionalities.

Conclusion

Growing data is a reality of modern networks, and analyzing this data is the key to business success. It’s therefore essential for operators to devise and optimize their analytics system and continuously measure its maturity, especially as cloud technology permeates.

5G data analytics functions and AI/ML are set to disrupt the way we design and operate our networks. High compute and 5G network speeds make it easier to analyze huge amounts of data and transmit the results in real-time.

AI and ML technologies also enable the development of more sophisticated data analytics systems that can do more than analyze data and relay information. These intelligent systems can perform self-assessments, auto-adjust, and perform complex tasks on their own, without needing human intervention. As we see more widespread adoption, they will be transformative for the industry.

Why 5G demands new charging capabilities  

5G’s transformative features such as low latency, ultrafast speeds, and high bandwidth open a world of opportunities for consumer and industry applications. Its ability to support massive volumes – according to Statista, 50 billion internet of things (IoT) connected devices are expected to be in use by 2030 – also unlocks the full potential of the Internet of Things (IoT). An operator’s charging capabilities thus assume a pivotal role, ensuring all 5G services are fully monetizable using modern and advanced charging use cases.

The charging engines many operators use today were designed for networks like 3G and LTE. These previous generations did not have the network scalability and performance needs of 5G, and are unable to support the advanced monetization capabilities that 5G use cases require to accurately charge across a large number of services, devices, and different event types. This demands fundamental changes to the underlying monetization architecture, taking a service-based approach, much like the 5G core network itself.

How next-gen charging capabilities work

Implementing next-gen charging and policy control functions of the 5G core enables operators to truly harness the monetization potential of 5G. The Charging Function (CHF) enables operators to charge for everything, supporting models for multiple parties (for instance, B2B2X models), helps implement RESTful processes, and enables real-time charging on various types of events. The Policy Control Function (PCF) enables end-to-end policy management, implements slice-based policies for highly specific applications, supports innovation and enrichment through service exposure, and offers advanced analytics for improved services.

In recent years, more and more operators have implemented converged charging for all their services, which is also part of the 3GPP Release 15 standard. The CHF has been functionally and architecturally restructured for 5G versus its legacy OCS counterpart. Supporting both online as well as offline charging, it is crucial to enabling 5G service providers to swiftly respond to evolving customer demands and introducing new and innovative services that can be charged. It implements network integrations that are formulated in keeping with service-based architecture, enabling next-gen monetization opportunities, employing cloud-based and containerized technology, enabling more automation, agility, flexibility, and minimizing revenue leaks.

Through network slicing, 5G operators can provide “slices” or smaller dedicated parts of their networks to customers, dedicating resources depending on the SLA to focus on speed, latency, capacity, and so on, supporting use cases such as smart buildings, smart offices, private campus networks, connected vehicles, and much more, all of which require charging support. Plus, 5G works on microservices-based infrastructure that helps deliver ultra-low latency, and to enable this, previously centralized charging components will now need to be more distributed and move closer to the network edge. So, 5G charging systems are required to support various new types of services like API calls, tiered QoS plans, edge computing capacity, and more.

Modern and scalable convergent charging systems assume particular relevance for enterprises, enabling a gamut of new-age applications to help businesses differentiate themselves while swiftly unlocking these new revenue streams. In the coming years, as 5G standalone deployments become more widespread, converged charging is expected to be more widely implemented.

5G charging use cases

5G supports a wide range of B2B, B2C, as well as B2B2X services, and thus demands charging use cases that help ensure zero revenue leakage across services. These include charging based on:

Slices

Network slicing is a key 5G use case and is integral to 5G charging. Most devices today have the same bandwidth and service levels, but network slicing creates new charging opportunities by enabling the segregation of network resources. Operators can provide slices to cater to a wide range of customer requirements, offering endless possibilities for revenue streams. Using flexible charging models, operators can monetize these slices for both direct consumers as well as the enterprise. Operators can offer various granular and personalized services to consumers on different slices. And for the enterprise customer, operators can offer models for different needs like IoT-connected devices and equipment, for its employees, its customers, special events, field tests and trials, and so on, for which unique policy and charging rules can be defined.

Network slices can be created based on various criteria, some of which include:

QoS tiers

Operators can charge subscribers based on the Quality of Service (QoS) they have signed up for. This is particularly relevant for industrial and enterprise applications, empowering the enterprise to define granular metrics such as latency, data rate, capacity, mobility, security, throughput, response time, level of service, and more.

SLA-based services

Network slices are designed to serve individual customer needs, for metrics including system capacity, user experience, energy consumption, coverage, latency, and more. The Service Level Agreement (SLA) will be defined based on the level of service a customer expects from each slice. 5G charging systems enable operators to dynamically scale pricing, define policy rules for specific devices, and much more, enabling them to offer more specific SLAs.

Platform use (PaaS)

Operators can build their own platforms and use open APIs to share and charge for their network and IT infrastructure with platform providers or developers who can use cloud infrastructure to deploy applications. The customer has control over the application, but the operator controls the underlying infrastructure.

Software use (SaaS)

In this case, the operator can charge for applications that it runs on the cloud and provides to consumers. The operator controls and manages both the infrastructure as well as the application and can charge on different events like time or usage.

Infrastructure use (IaaS)

Service providers can partner with enterprises to share their infrastructure and/or applications, granting the enterprise control over this infrastructure while charging for its use. This is especially useful for smaller enterprises who do not want to invest in their own infrastructure but are in need of a secure and private network.

Digital ecosystems

Operators can set up digital ecosystems or marketplaces to provide a platform that connects producers and providers of goods and services with consumers, forging partnerships with these providers to monetize the service. Here, operators have the added advantage of having access to advanced data and analytics tools that help them segregate customers, run targeted campaigns, and more.

Real-time performance

5G’s ultrafast speeds, stable connectivity, and low latency enable real-time applications, including multimedia like augmented reality, virtual reality, and gaming. Operators can define charging based on real-time performance for these applications.

Benefits of next-gen charging systems 

5G charging engines offer a host of benefits to operators, enabling them to swiftly adapt to dynamic market needs. Some of these include:

Handle advanced 5G use cases 

With the rapid increase in the number of devices connected to the network, 5G charging systems must handle an unprecedented amount of traffic and charge for the endless application possibilities of next-gen networks. 3GPP has defined a host of possibilities for the 5G charging ecosystem, introducing elements in the 5G core that are unavailable in legacy charging systems. The PCF serves as a unified platform to govern the implementation of policy and charging rules. The Session Management Function enables operators to seamlessly implement session charging between devices, so they can efficiently charge users when they use different devices for the same service, for instance, like watching a movie. And other network functions, such as the Network Exposure Function (NEF), Access and Mobility Management Function (AMF), and Network Slice Management, equip operators to gather essential device and location data, implement slice-based charging, enable multiple flexible charging scenarios, facilitate operators and enterprises to share session information, allow granular charging based on advanced analytics, and more.

Develop diverse partnerships

5G charging capabilities include support for multiple business partners on a single platform, enabling operators’ business and marketing teams to easily and dynamically forge innovative partnerships to monetize B2B2X, B2B, B2C, wholesale, and IoT services.

Enhance customer experience

By making a host of advanced use cases fully monetizable, 5G charging paves the way for innovation, boosting CX, improving brand differentiation, and ensuring customer loyalty.

High return on investment

Advanced charging helps open new revenue streams as well as secure the revenue potential of existing services, maximizing ROI.

Improve business agility

Operators can effortlessly launch new plans and promotions, automate transaction processing even for the most complex use cases, implement flexible data models that support complex account hierarchies for granular plans and services, and more.

How Alepo can help 

Alepo supports advanced charging use cases through robust convergent charging and policy control network functions, both of which are part of the 5G-compliant Digital BSS product suite and Alepo’s 5G Core Network solution. Both can either be deployed as part of the new solution or integrated with any other vendor’s BSS, enabling you to preserve your existing network investments.

Legacy 4G/LTE environments are unable to support charging for 5G use cases, so the first step towards implementing advanced charging is ensuring you have a modern BSS and 5G Core infrastructure. As experts in this domain, Alepo can provide a host of deployment options to smoothly transition to 5G, including local, public, hybrid, 4G + 5G combo, and private models.