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5G Standalone in action – the power of programmability and interoperability

Mark Chong, Deputy CEO of Thailand’s AIS, talks to Contributing Editor Annie Turner about the drivers of automation, fighting the IT stack and the importance of speed. 

Mark Chong became Deputy CEO of Thailand’s mobile operator Advanced Info Service (AIS) in December 2022. Previously he worked at Singtel for more than two decades, most recently in the role of Global CTO for almost six years. Singtel holds a 24.99% stake in Intouch Holdings, AIS’ parent company. Singtel is regarded as one of the world’s most advanced telcos, thriving in one of the fastest growing and most dynamic regions. Experience and expertise is definitely not lost in translation between the two.

Like Singtel, AIS has deployed 5G Standalone which Chong states “drives more automation because without automation, it becomes humanly impossible to handle all the various tasks”. He adds, “There’s a big difference between 4G and 5G: with 5G the network becomes programmable and there are more network elements for engineers to handle. When something breaks, how do you deal with that?”

“We really need to automate all the manual, mundane, trivial stuff to enable engineers to focus on the more sophisticated pieces of engineering,” Chong says.

At Singtel, Chong’s team created zero-touch trouble tickets, sending tickets into the field and began automating recovery of circuits to reduce the back-end’s workload. “We did things like automating our collection of firewall policies and their configuration to reduce labour – things that normally took a few hours came down to a matter of minutes,” he says.

AIS is taking a similar approach with trouble tickets to shorten recovery times, but first-call resolution is a big priority too. To help achieve this, data analytics of various network metrics are fed directly to call centre agents which also speeds up call handling.


Programmable, interoperable

Along with being programmable, 5G has other new capabilities, like orchestration, network slicing and the ability to expose network commands to third-parties including customers. “Manufacturing clients, for example, now want some say about how the network performs,” he explains. “5G networks can operate on commands generated from the customer’s network – under certain circumstances and conditions, of course – but when things break, where’s the cause?”

Chong gives real, commercial examples of interoperable scenarios: Singtel deployed its 5G infrastructure network solutions at a car manufacturing facility in Singapore. The radio coverage within the factory drives manufacturing processes. The same solution, which runs on Singtel’s Paragon orchestration platform, is used in vehicle manufacture in Thailand to monitor the power current.

AIS is also implementing a discrete, private 5G network for an open mining company. The above-ground network will drive autonomous excavators via communication links. He suggests a similar approach could be deployed in ports, which have many containers and also rely on automatic guided vehicles. However, Chong stresses, “Each customer has its own requirements so we have to listen to them and see how we can adapt our solution to suit their needs”.


Rethinking the IT stack

Interweaving customers’ networks into their own 5G infrastructure means most telcos must fundamentally rethink their IT stacks. “If we don’t, it is impossible to support all these new requirements at the required speed,” Chong says.

“The OSS needs to be the right set of metrics and measurements; processes need to be reinvented, rethought,” he continues. A simple example is that previously, field workers were not dispatched to a customer’s premises if something went wrong whereas now “we have started to employ enhanced radio in a car factory and the private network in the mine…I need to provide field operational support for these installations. I must change the structure of my support teams for customers,” he comments.

“We must change what we measure around that radio in the field and be able to pipe [operational information] to the customer’s dashboard because now business mission-critical processes run on the network.”

How far is AIS on its network automation journey? He replies, “I’d say it’s in its early stages but moving in the right direction. One of the issues is our monolithic IT stack. To introduce new capabilities requires investment in resources and quite a bit of effort. It’s not just about having a modular OSS, but the whole modular IT stack, including billing and your front-end digital shop – wherever you’re seeing customers, from the cradle to the grave, in the BSS and for omnichannel.”


APIs and making radical changes

At FutureNet Asia 2023 Mark Chong will be on the panel: Operational transformation – Accelerating the journey to zero-touch automation

These radical moves cannot be made overnight. AIS’ approach is to introduce application program interfaces (APIs) in certain segments of the stack to link various parts for internal use. He elaborates, “Likewise, you need open APIs to interoperate with the customer’s network, to introduce new capabilities, new elements into your network.

“As a brownfield operator, we need a new reference architecture, so we’re running an architecture at two speeds. You have to create a new mediation layer or new enterprise service bus and progressively migrate elements onto it. The telcos must control the architecture, the enterprise service bus and the open, standard APIs to connect new boxes to the bus. You can get an outsourcer to build it, but the CIO or CTO must control which elements come into their network and how you hook them up.”

What does he mean when he refers to open APIs? Chong explains, “Singtel is a member of the GSMA board and one of the founders of its Open Gateway. Prior to that, we had embarked on the adoption of TM Forum’s Open APIs.

“One of the things we are very loud about is that CAMARA [which is part of the Open Gateway initiative to support abstracting from network APIs to service APIs] should be compatible with or should absorb TM Forum’s APIs into its larger set because many telcos and companies have already adopted them and we should not reinvent the wheel.

“We should focus very much on having a unified, harmonious, federated outcome that enables companies to go to market quickly and introduce new use cases. It’s less about who has the right technology, but rather, let’s bring the benefits of 5G’s programmability and operability across various systems and platforms to benefit customers.”


Becoming cloud native

This pragmatism extends to AIS’ approach to cloud. “We are largely working with our network vendors as we cannot do it all by ourselves – and they have gone into telco cloud. Are they ‘truly native’ like the OTT hyperscalers? I would say not to the same level…but good enough,” Chong says.

He points out that the various global cloud and network equipment providers each have their own approach. “Some of them tried to be the universal transporter or handler of workloads from one cloud to another. VMware does that quite well, but the rest are pretty proprietary,” Chong says.

“Each cloud provider brings the benefits of agility, resiliency, scale but in their own proprietary way and the commercials of each cloud are different, so you must go in with your eyes open.…You have to think through what could go into the cloud and what should not. If you have to refactor applications [for them to become cloud native] that’s a big chunk of work. Some are better left alone; for others with a longer runway, it’s worth the effort.”


AI to benefit customers

How much will the use of AI, including generative AI, be instrumental in automation and delivering benefits to customers? Chong says while he is very interested in generative AI’s potential it is immature but he believes it will raise productivity.

For now, machine learning (ML) is the most common type of AI used by AIS (and many other telcos), such as “in the go-to-market piece,” Chong says. “We analyse data to build as much of a 360-degree customer profile as possible, then we cook up campaigns and come up with bundles for next best offers” proffered via the digital channel or store the customer choses.

Chong thinks AI could speed up handling queries from customers about promotions or their bills. “We will train a model to understand our policies and handle customers’ requests,”. He adds, “We have an AI-enabled voice robot that can conduct a human-like conversation when reminding customers about payment. We are in the final trial stages and it should be launched soon, for consumers and enterprise customers.”

ML also correlates alarms to engineers who can more quickly identify and focus on the root causes among the “ocean of alarms”. Singtel deploys cognitive technology to gather data about customers’ use of fixed broadband deployments and data analysis for preventive maintenance such as rebooting modems before their memory fills up, easing congestion.


The benefits of hindsight and speed

What would Chong do differently if he were starting over with network automation? He muses, “The end goals remain the same but we could have done better by bringing more people on board within the organisation, getting teams installed faster, learning new technologies faster. When we started, we were a bit tentative in trials and tests.

“We’re now more certain that we are on the right path. We’ve put things in place that have greatly improved our processes, reduced development time, etc. We’re now bringing on more parts of the organisation as they can see what we’ve done and are onboard.”

Mark Chong will be on the panel discussing Operational transformation: Accelerating the journey to zero-touch automation at FUTURENET ASIA in Singapore 18 & 19 October, at 4pm on Day 1.

Industrial internet users increasingly rely on telecom-tech orchestrators, says Telenor Asia business and partnerships chief

Contributed by Eugene Teh Yee, SVP, Head of Business and Partnerships, Telenor Asia & keynote speaker at FutureNet Asia 2023.

Telenor Asia recently closed the two largest telecom mergers in Southeast Asia. These mega-deals come at a time of rapid transformation in the region: fast-growing data usage, billions of connected devices, and the rise of new technologies such as 5G and machine learning. As Telenor Asia’s Head of Business and Partnerships, Eugene Teh has a firm grasp on how these changes are affecting Asia. We asked him why Telenor Asia sees the need for bigger, stronger digital champions in Asia and how Telenor Asia’s scale helps the telco operators in their portfolio deliver new solutions to customers, businesses, and governments.

“We’re at a juncture in Asia. 5G is starting to reshape the landscape. There are ambitious digital transformation agendas at the national level and more pressure on businesses, too. Who can best enable these changes? Within the tech ecosystem, Telenor Asia’s operating companies are local, they are strong brands, and they are trusted,” says Teh. “This puts them in an ideal position to support the digital transformation of their local partners.”

Teh believes this opportunity requires that telecom operators evolve from pure connectivity providers to technology orchestrators, rapidly bringing together platforms and network solutions to develop new capabilities to better serve enterprises.

“Telenor Asia is looking at the next horizon, where value will be created tomorrow.”

Eugene Teh, Head of Business and Partnerships, Telenor Asia

“We think of 5G as the industrial internet and Telenor Asia’s operating companies are already working on big scale enterprise projects in many sectors. In the energy and shipping industries, they’ve built internet of things platforms for safer and smarter logistics. In banking and retail, they have solutions to digitalize and streamline the many touchpoints,” he says. “In each case, the solutions are tailored to each enterprise’s requirements. They’re able to anchor a project that is using multiple sub-systems and still deliver a solution very quickly.”

In Thailand and in Malaysia, Telenor Asia owns roughly a third of each market’s leading operator: True Corporation and CelcomDigi. The latter is now collaborating with Petronas to equip its offshore platforms with full wireless connectivity—a first in Asia. In Thailand, True Corporation was recently awarded GSMA’s 5G Living Challenge award for a use case at Siriraj Hospital that is saving lives with connectivity solutions that track ambulances and applies machine learning to the triage process.

“It’s about bringing multiple pieces together as an enterprise solution is complicated,” says Teh. “And this is where Telenor Asia can take local operators to the next level. For an initial proof-of-concept for offshore connectivity in Malaysia, we called on Telenor Maritime, who have very extensive experience providing robust connectivity in very demanding environments. In a smart meter use case, we partnered with Telenor IoT to connect devices across operators. Our scale also allows us to establish stronger partnerships with hyperscalers when needed. That mix of strong local presence and global scale is Telenor Asia’s strength.”

Telenor Asia also brings a longer perspective on where connectivity is headed. As the former Head of Business at digi (now CelcomDigi), Eugene Teh recalls that the focus in-market tends to be on immediate needs and existing business opportunities. In his role at Telenor Asia, he can get ahead of those needs.

“Telenor Asia is looking at the next horizon, where value will be created tomorrow. A lot of future value will be in large scale industrial use cases using a combination of technology (5G, cloud, edge computing, AI etc), with the right infrastructure, right partners and understanding of local regulations. Telenor Asia is spotting where the next opportunities will be and preparing the partnerships and solutions that will allow our operating companies to have products on hand when their market is ready,” says Teh. “It can make the difference between playing catch-up and being the first one ready to deliver.”

To achieve this ambition, Teh underscores the need for new structures that can capitalize on opportunities more quickly. This is why Telenor Asia, in addition to its recent mergers, continues its exploration of how to become even more agile.

“Telenor Asia has put the pieces together to make this work: market-leading positions, links to the best partners globally, and a nimbler organisation structure. The result is that we have strong, local, digital champions; and an owner in Telenor Asia with the right capabilities to back them up,” Teh concludes.

  • Coming soon: Can Asia get ahead of the AI race? We asked an expert who advises the EU and heads AI research at Telenor 
  • Coming soon: Energy challenge from Asia’s fast-rising data usage calls for new thinking says Telenor Asia head of tech

For more insights from Telenor Asia, visit here

AI rises up the network automation agenda

Contributing Editor Annie Turner rounds up the summer’s news headlines and notes how AI is moving beyond ML and positioned to unlock telcos’ data to speed automation

Heavy Reading has published a timely and, as far as we know, the first study into the future of network automation for Tier 2 and Tier 3 network operators. They are defined here as having revenues of less than $1 billion annually. The survey was commissioned by Juniper Networks, with responses from 217 Tier 2 and 3 execs around the globe – a far bigger sample than the average study.

What are the primary drivers for implementing automation in your network? (Select the top three)

For 30% of those surveyed, most operations are almost entirely manual, relying on command-line interfaces and other legacy software: closed loop and higher levels of automation are very rare, regardless of the size of the operator within the definition. Only 6% say they have fully autonomous, self-driving network automation.

The issue isn’t that these operators don’t understand the potential of automation for both customer-facing and internal, network-centric purposes, as the graph shows.

It’s just that it’s too difficult for a whole lot of reasons, not all of which have to do with technology. For example, the third biggest hurdle (named by 29% of respondents) is internal resistance due to the fear the automation will cut jobs and another is a lack of clarity about automation’s objectives. The the report looks at the role of SaaS, cloud and AI in network automation. Read on for how the elements of the industry are, via various routes, striving to address some of those obstacles.


Democratising AI?

Nvidia CEO and founder, Jensen Huang

VMware made a clutch of announcements at the opening of its VMware Explore event in Las Vegas in August. They included “new Private AI offerings to drive enterprise adoption of generative artificial intelligence,” and expanded its relationship the world’s biggest maker of silicon for AI, NVIDIA. It launched the VMware Private AI Foundation with NVIDIA. This, VMware said, puts the power of generative AI within the reach of any enterprise.

The chip-maker’s CEO and founder, Jensen Huang, echoed this in his presentation at the event: “Our expanded collaboration with VMware will offer hundreds of thousands of customers – across financial services, healthcare, manufacturing and more – the full-stack software and computing they need to unlock the potential of generative AI using custom applications built with their own data.”


Breaking data barriers

This interesting in the light of a the Heavy Reading survey and one carried carried out by Analysys Mason earlier this year of 84 telco execs from around the world. It was commissioned by Nokia and the main finding was that one of the biggest hurdles is integrating AI into heterogeneous networks is that access to high-quality data sets is hampered by legacy systems with proprietary interfaces. It also found that high costs mean some operators are not investing in AI platforms.

Enter the Global Telco AI Alliance. It was formed at the end of July by Deutsche Telekom, e& and Singtel to accelerate telcos’ AI transformation in telcos and develop new AI-powered business models. The memorandum of understanding between the parties includes the co-development of a Telco AI Platform.

Just a couple of weeks later, SKT again underlined its commitment to AI and to producing assets for use by other operators, announcing it had invested $100 million in AI firm Anthropic to build a large language model (LLM) customised for telcos. Anthropic had already raised $450 million from Google and Spark Capital in May.


VMware edges closer to Broadcom

Circling back, VMware seems closer to being acquired by Broadcom, having secured approvals for the proposed deals in many countries, most recently from the UK’s Competition Market Authority in August. The proposed deal was announced last summer but wasn’t greeted by much enthusiasm by Wall Street which didn’t see the logic of the transaction.

One school of thought is that chip-maker Broadcom plus VMware’s cloud and virtualisation software could bridge the gap between the data centres it powers and the applications that run in them. As Tom Nolle writes, “The data center used to be the focus, the resource that ran everything. Today, I’d argue that virtualization and the cloud have gotten us back to where our focus needed to be – the applications that support businesses.”

It’s worth noting that China has yet to pronounce on the proposed acquisition. There are suggestions that if it objects, the deal could be scuppered. Broadcom’s CEO, Hock Tan, has dismissed those concerns.


Finally, back in the here and now, BT is running a proof of concept (PoC) with French firm Infovista which specialises in network lifecycle automation. The aim is to reduce interruptions to voice services through faster identification of root causes, shorter mean times to resolution and greater customer satisfaction. Infovista said it generally expects to cut resolution times by more than two-thirds for network operators through an automated workflow.

In the PoC workflow detects issues, carries out analyses and generates alarms within BT’s trouble-ticketing system. The alarms embed data to streamline troubleshooting of issues in the network and services, and that are subscriber related. The tech should also reduce operational costs as there is no need for level 1 support or fast-tracking issues to the right level 2 teams, according to the vendor.

This is about shifting from manual to automated operations that are governed by key performance indicators and service level agreements to maintain service and business objectives.




Precision Timing When Every Second Counts

Contributed by Chris Moezzi, Vice President and General Manager of Foundational NIC, IP, and Customer Solutions, Intel Corporation.

Have you ever seen a crew performing a pit stop in a motor race? How about when one of the pit crew members fails to keep pace with the others, causing a delay in the pit stop? In a sport where fractions of a second can mean winning or losing a race, the synchronization and accuracy of the pit crew members (not just the driver) play a critical role in the outcome of a race.

Staying at the Forefront of 5G vRAN Transformation

Time is a valuable element of 5G virtualized radio access network (vRAN) performance. To use a real-world example, in the same manner synchronization and accuracy are key ingredients to the performance of a motor race “pit crew,” time synchronization in 5G vRAN plays an equally critical role in network performance and end-user 5G experiences in their everyday lives. Through the RAN, end-users use their cell phones to browse the web, use an app, or make a phone call. As 5G continues to evolve, new use cases continue to emerge, calling for low-latency and precision timing capabilities as part of a cost-effective solution. Intel enables communication service providers (CoSPs) to stay at the forefront of 5G vRAN transformation and deliver new or improved capabilities and services.

The new Intel® Ethernet 800 Series Network Adapters E810-CQDA2T (formerly codenamed Logan Beach) and E810-XXVA4T (formerly codenamed Westport Channel) are optimized for deployments from the cloud to the 5G edge by offering advancements that simplify timing synchronization and greater timing accuracy. HW-enhanced 1588 precision time protocol (PTP) and Synchronous Ethernet (SyncE) support featured on these adapters enhance the timing synchronization with other parts of 5G vRAN infrastructure. These advancements and innovations improve timing synchronization and present benefits to end-user applications.

Intel® Ethernet 800 Series Network Adapters E810-CQDA2T and E810-XXVA4T

Timing Synchronization in Emergency Location Services

Take, for example, Enhanced 911 (in the United States) or eCall (999 in Europe) services. Using trilateration, a technique that detects the timing delay between different cell towers, emergency responders can pinpoint an emergency caller’s relative location within a given radius.

In the past, 3G applications could identify an emergency caller’s location within approximately a 100-meter radius. With the improved timing hardware implemented in 4G RAN, an emergency caller’s location radius could be reduced to approximately 50 meters. Now, thanks to HW-Enhanced 1588 PTP and SyncE, the E810-CQDA2T and E810-XXVA4T adapters can maximize timing accuracy and minimize timing variance in cell site synchronization to tighten an emergency caller’s location radius even further to approximately 30 meters over 5G vRAN [1].

HW-Enhanced 1588 PTP and SyncE in the E810-CQDA2T and E810-XXVA4T Intel® Ethernet Network Adapters can tighten a caller’s location radius to approximately 30 meters over 5G vRAN.

Timing synchronization for 5G vRAN solutions requires a substantial degree of accuracy. Should the infrastructure for timing synchronization be insufficient, end-users can experience poor services and frequent disruptions, resulting in dropped calls, poor video quality, and in the context of our example use case, inaccurate location services. When every second counts in an emergency situation, improving and accelerating the delivery of location services is crucial to increasing the success rate of emergency response. As a synchronized and highly accurate pit crew can help win a motor race, so too can accurate timing synchronization in 5G vRAN help bring a successful response to an emergency.

At this year’s Mobile World Congress (MWC) in Barcelona, come see a demonstration of this use case at the Intel booth located in Hall 3, Stand #3E31. We’ll present how vRAN timing synchronization increases the accuracy of emergency location services and discuss the key features of the E810-CQDA2T and E810-XXVA4T Intel® Ethernet Network Adapters. We’ll even have samples available at the kiosk for you to take a closer look at these adapters.

Meet Intel at FutureNet Asia, 18/19 October 2023, Singapore

Trusted Solutions for 5G vRAN Infrastructure

Intel’s unmatched portfolio demonstrates our commitment to innovate and deliver the most trusted solutions for 5G vRAN infrastructure. Set to launch at MWC Barcelona 2023, 4th Gen Intel® Xeon® Scalable Processors with Intel® vRAN Boost offer CoSPs the ability to boost networks by enabling programmable infrastructure and eliminating the need for custom vRAN accelerator cards. With forward error correction (FEC) acceleration directly integrated into these processors, CoSPs can maintain reliable service through detection and correction of transmission errors with reduced power consumption and total cost of ownership.

Combine these features with those found in E810-XXVDA4T or E810-CQDA2T Intel® Ethernet Network Adapters, and CoSPs can deploy a 5G vRAN solution with hardware-enhanced timing synchronization capabilities that meet stringent vRAN requirements while eliminating the need for expensive, dedicated timing appliances. In dense radio configurations, CoSPs can add the Intel® vRAN Accelerator ACC100 Adapter for increased capacity through its concurrent 5G and 4G FEC acceleration, integrated Intel® FlexRAN software reference architectures, and support of cloud native, VM, and bare metal.

Watch this video to see how Intel’s portfolio of solutions for vRAN come together to maximize vRAN transformation.

Intel’s solutions for vRAN enable flexible and scalable platforms that deliver high timing accuracy and FEC acceleration, avoid vendor lock-in by removing the need for expensive proprietary systems, and reduce total cost of ownership. Intel continues to provide and evolve solutions for vRAN in pursuit of delivering innovations that address the many challenges faced by CoSPs, including timing synchronization precision in 5G vRAN ecosystems. It’s why more than 90% of today’s commercial vRAN networks around the world run on Intel architecture [2].

As the driver is a key factor to the success of a racing team, the other members, like the pit crew, racing strategists, and engineers, are significant contributors to the overall outcome of a race. When the entire team comes together, in sync and focused, the team’s performance is exponentially greater. With 4th Gen Intel® Xeon® Scalable Processors in the driver seat and the pit crew of Intel® Ethernet 800 Series Network Adapters ready to ensure the car connects through every corner of the racetrack, Intel’s portfolio of solutions for vRAN come together to optimize the potential of earning a place on the podium.

Discover how Intel® Solutions for vRAN enable CoSPs to build vRAN solutions that meet unique customer needs with accelerated time to market deployment by visiting intel.com/ethernet.

Notices & Disclaimers:

Performance varies by use, configuration, and other factors. Learn more on the Performance Index site.

Performance results are based on testing as of dates shown in configurations and may not reflect all publicly available updates. See backup for configuration details. No product or component can be absolutely secure.

Intel technologies may require enabled hardware, software or service activation.

Your costs and results may vary. Code names are used by Intel to identify products, technologies, or services that are in development and not publicly available. These are not “commercial” names and not intended to function as trademarks.

© Intel Corporation. Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.


1. Qualcomm Technologies, Inc. report published August 7, 2014, “Introduction to OTDOA on LTE Networks.”

2. Dell’Oro report published in Jan. 2023, “Mobile RAN Five-Year Forecast Report 2023–2027 Vol.22 №1,” with Intel analysts.

Header Photo by gustavo Campos on Unsplash

What is Happening in the Network Edge

Contributed by Dell Technologies.

Where is the Network Edge in Mobile Networks

The notion of ‘Edge’ can take on different meanings depending on the context, so it’s important to first define what we mean by Network Edge. This term can be broadly classified into two categories: Enterprise Edge and Network Edge. The former refers to when the infrastructure is hosted by the company using the service, while the latter refers to when the infrastructure is hosted by the Mobile Network Operator (MNO) providing the service.

This article focuses on the Network Edge, which can be located anywhere from the Radio Access Network (RAN) to next to the Core Network (CN). Network Edge sites collocated with the RAN are often referred to as Far Edge.

What is in the Network Edge

In a 5G Standalone (5G SA) Network, a Network Edge site typically contains a cloud platform that hosts a User Plane Function (UPF) to enable local breakout (LBO). It may include a suite of consumer and enterprise applications, for example, those that require lower latency or more privacy. It can also benefit the transport network when large content such as Video-on-Demand is brought closer to the end users.

Modern cloud platforms are envisioned to be open and disaggregated to enable MNOs to rapidly onboard new applications from different Independent Software Vendors (ISV) thus accelerating technology adoption. These modern cloud platforms are typically composed of Commercial-of-the-Shelf (COTS) hardware, multi-tenant Container-as-a-Service (CaaS) platforms, and multi-cloud Management and Orchestration solutions.

Join Dell Technologies at FutureNet Asia, 18/19 October 2023, in Singapore

Similarly, modern applications are designed to be cloud-native to maximize service agility. By having microservices architectures and supporting containerized deployments, MNOs can rapidly adapt their services to meet changing market demands.

What contributes to Network Latency

The appeal of Network Edge or Multi-access Edge Computing (MEC) is commonly associated with lower latency or more privacy. While moving applications from beyond the CN to near the RAN does eliminate up to tens of milliseconds of delay, it is also important to understand that there are many other contributors to network latency which can be optimized. In fact, latency is added at every stage from the User Equipment (UE) to the application and back.

RAN is typically the biggest contributor to network latency and jitter, the latter being a measure of fluctuations in delay. Accordingly, 3GPP has introduced a lot of enhancements in 5G New Radio (5G NR) to reduce latency and jitter in the air interface. We can actively reduce latency through the following categories: There are three primary categories where latency can be reduced:

  • Transmission time: reduce symbol duration with higher subcarrier spacing or with mini slots
  • Waiting time: improve scheduling (optimize handshaking), simultaneous transmit/receive, and uplink/downlink switching with TDD
  • Processing time: reduce UE and gNB processing and queuing with enhanced coding and modulation

Transport latency is relatively simple to understand as it is mainly due to light propagation in optical fiber. The industry rule of thumb is 1 millisecond round trip latency for every 100 kilometers. The number of hops along the path also impacts latency as every transport equipment adds a bit of delay.

Typically, CN adds less than 1 millisecond to the latency. The challenge for the CN is more about keeping the latency low for mobile UEs, by seamlessly changing anchors to the nearest Edge UPF through a new procedure called ‘make before break’. Also, the UPF architecture and Gi/SGi services (e.g., Deep Packet Inspection, Network Address Translation, and Content Optimization) may add a few additional milliseconds to the overall latency, depending on whether these functions are integrated or independent.

Architectural and Business approaches for the Network Edge

The physical locations that host RAN and Network Edge functionalities are widely recognized to be some of the MNOs’ most valuable assets. Few other entities today have the real estate and associated infrastructure (e.g., power, fiber) to bring cloud capabilities this close to the end clients. Consequently, monetization of the Network Edge is an important component of most MNOs’ strategy for maximizing their investment in the mobile network and, specifically, in 5G. In almost all cases, the Network Edge monetization strategy includes making Network Edge available for Enterprise customers to use as an “Edge Cloud.” However, doing so involves making architectural and business model choices across several dimensions:

  • Connectivity or Cloud: should the MNO offer a cloud service or just the connectivity to a cloud service provided by a third party (and potentially hosted at a third party’s site).
  • aaS model: in principle, the full range of as-a-Service models are available to the MNO to offer at the network edge. This includes co-location services; Bare-Metal-as-a-Service, Infrastructure-as-a-Service (IaaS), Containers-as-a-Service (CaaS), and Platform and Software-as-a-Service (PaaS and SaaS). Going up this value chain (up being from co-lo to SaaS) allows the MNO to capture more of the value provided to the Enterprise. However, it also requires it to take on significantly more of responsibility and puts it in direct competition with well-established players in this space – e.g., the cloud hyperscale companies. The right mix of offerings – and it is invariably a mix – thus involves a complex set of technical and business case tradeoffs. The end result will be different for every MNO and how each arrives there will also be unique.
  • Management framework: our industry’s initial approach to exposing the Network Edge to the enterprises involved a management framework that tightly couples to how the MNO manages its network functions (e.g., the ETSI MEC family of standards for example (ETSI MEC)). However, this approach comes with several drawbacks from an Enterprise point of view. As a result, a loosely coupled approach, where the Enterprise manages its Edge Cloud applications using typical cloud management solutions appears to be gaining significant traction, with solutions such as Amazon’s Wavelength as an example. This approach, of course, has its own drawbacks and managing the interplay between the two is an important consideration in Network Edge (and one that is intertwined with the selection of aaS model).
  • Network-as-a-Service: a unique aspect of the Network Edge is the MNOs ability to expose network information to applications as well as the ability to provide those applications (highly curated) means of controlling the network. How and if this makes sense is again both an issue of the business case – for the MNO and the Enterprise – as well as a technical/architectural issue.

Certainly, the likely end state is a complex mixture of services and go-to-market models focused on the Enterprise (B2B) segment. The exposition of operational automation and the features of 5G designed to address this make it likely that this is a huge opportunity for MNOs. Navigating the complexities of this space requires a deep understanding of both what services the Enterprises are looking for and how they are looking to consume these. It also requires an architectural approach that can handle the variable mix of what is needed in a way that is highly scalable.

As the long-time leader in Enterprise IT services, Dell is uniquely positioned to address this space – stay tuned for more details in an upcoming blog!

Building the Network Edge

There are several factors to consider when moving workloads from central sites to edge locations. Limited space and power are at the top of the list. The distance of locations from the main cities and generally more exposed to the elements require a new class of denser, easier-to-service, and even ruggedized form factors. Thanks to the popularity of Open RAN and Enterprise Edge, there are already solutions in the market today that can also be used for Network Edge. Read more on Edge blog series Computing on the Edge | Dell Technologies Info Hub

Higher deployment and operating costs are another major factor. The sheer number of edge locations combined with their degraded accessibility make them more expensive to build and maintain. The economics of the Network Edge thus necessitates automation and pre-integration. Dell’s solution is the newly engineered cloud-native solution with automated deployment and life-cycle management at its core. More on this novel approach here Dell Telecom MultiCloud Foundation | Dell USA.

Last is the lower cost of running applications centrally. Central sites have the advantage of pooling computes and sharing facilities such as power, connectivity, and cooling. It is therefore important to reduce overhead wherever possible, such as opting for containerized over VM-based cloud platforms. Moreover, having an open and disaggregated horizontal cloud platform not only allows for multitenancy at edge locations, which significantly reduces overhead but also enables application portability across the network to maximize efficiency.

The ideal situation is where Open/Cloud RAN and Network Edge are sharing sites thus splitting several of the deployment and operations costs. Due to the latency requirements, Distributed Unit (DU) must be placed within 20 kilometers of the Radio Unit (RU). Latency requirements for the mid-haul interface between DU and Central Unit (CU) are less stringent, and CU could be placed roughly around 80-100 kilometers from the DU. In addition, the Near-Real Time Radio Intelligent Controller (Near-RT RIC) and the related xApps must be placed within 10ms RTT. This makes it possible to collocate Network Edge sites with the CU sites and Near-RT RIC.


What has happened over the past few years is that several MNOs have already moved away from having 2-3 national DCs for their entire CN to deploying 5-10 regional DCs where some network functions such as the UPF were distributed. One example of this is AT&Ts dozen “5G Edge Zones” which were introduced in the major metropolitan areas: AT&T Launching a Dozen 5G “Edge Zones” Across the U.S. (att.com).

This approach already suffices for the majority of “low latency” use cases and for smaller countries even the traditional 2-3 national DCs can offer sufficiently low transport latency. However, when moving into critical use cases with more stringent latency requirements, which means consistently very low latency is a must, then moving the applications to the Far Edge sites becomes a necessity in tandem with 5G SA enhancements such as network slicing and an optimized air interface.

The challenge with consumer use cases such as cloud gaming is supporting the required Service Level (i.e., low latency) country wide. And since enabling the network to support this requires a substantial initial investment, we are seeing the classic chicken and egg problem where independent software vendors opt not to develop these more demanding applications while MNOs keep waiting for these “killer use cases” to justify the initial investment for the Network Edge. As a result, we expect geographically limited enterprise use cases to gain market traction first and serve as catalysts for initially limited Network Edge deployments.

For use cases where assured speeds and low latency are critical, end-to-end Network Slicing is essential. In order to adopt a new more service-oriented approach, MNOs will need Network Edge and low latency enhancements together with Network Slicing in their toolbox. For more on this approach and Network Slicing, please check out our previous blog To slice or not to slice | Dell Technologies Info Hub.


About the author: Tomi Varonen 

Tomi Varonen is a Telecom Network Architect in Dell’s Telecom Systems Business Unit. He is based in Finland and working with the Cloud, Core Network, and OSS&BSS customer cases in the EMEA region. Tomi has over 23 years of experience in the Telecom sector in various technical and sales positions. Wide expertise in end-to-end mobile networks and enjoys creating solutions for new technology areas. Passion for various outdoor activities with family and friends including skiing, golf, and bicycling.


About the author: Arthur Gerona

Arthur is a Principal Global Enterprise Architect at Dell Technologies. He is working on the Telecom Cloud and Core area for the Asia Pacific and Japan region. He has 19 years of experience in Telecommunications, holding various roles in delivery, technical sales, product management, and field CTO. When not working, Arthur likes to keep active and travel with his family.



About the author: Alex Reznik 

ALEX REZNIK is a Global Principal Architect in Dell Technologies Telco Solutions Business organization.  In this role, he is focused on helping Dell’s Telco and Enterprise partners navigate the complexities of Edge Cloud strategy and turning the potential of 5G Edge transformation into the reality of business outcomes.  Alex is a recognized industry expert in the area of edge computing and a frequent speaker on the subject.  He is a co-author of the book “Multi-Access Edge Computing in Action.”  From March 2017 through February 2021, Alex served as Chair of ETSI’s Multi-Access Edge Computing (MEC) ISG – the leading international standards group focused on enabling edge computing in access networks.

Prior to joining Dell, Alex was a Distinguished Technologist in HPE’s North American Telco organization.   In this role, he was involved in various aspects of helping Tier 1 CSPs deploy state-of-the-art flexible infrastructure capable of delivering on the full promises of 5G.  Prior to HPE Alex was a Senior Principal Engineer/Senior Director at InterDigital, leading the company’s research and development activities in the area of wireless internet evolution.  Since joining InterDigital in 1999, he has been involved in a wide range of projects, including leadership of 3G modem ASIC architecture, design of advanced wireless security systems, coordination of standards strategy in the cognitive networks space, development of advanced IP mobility and heterogeneous access technologies and development of new content management techniques for the mobile edge.

Alex earned his B.S.E.E. Summa Cum Laude from The Cooper Union, S.M. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, and Ph.D. in Electrical Engineering from Princeton University. He held a visiting faculty appointment at WINLAB, Rutgers University, where he collaborated on research in cognitive radio, wireless security, and future mobile Internet.   He served as the Vice-Chair of the Services Working Group at the Small Cells Forum.  Alex is an inventor of over 160 granted U.S. patents and has been awarded numerous awards for Innovation at InterDigital.

Data is the new gold! Why data driven transformation puts you ahead of the game in Industry 4.0

Contributed by Lucky La Riccia, Head of Cloud Software & Services, Ericsson Middle East and Africa.

The ever-increasing pace of digital technology has transformed and created a new business climate that is moving faster than ever before. Unlike previous generations of the industrial revolution, Industry 4.0 is significantly transforming the way goods are produced and delivered and moving toward an industry that is fully connected and automated. The complexities of meeting customers’ needs have driven businesses to embrace the use of analytics to remain competitive and productive.

Data is the new gold in this technology-led era, and data-driven transformation places organizations ahead of the game. Adapting and implementing the best technology without pursuing data-driven transformation will still make an organization less competitive and in danger of going extinct.


Figure 1: Increasing complexity requires new technology for proactive & data-driven operations


Data-driven transformation is an organization’s ability to make better decisions leveraging data collected at various touchpoints from human-machine interactions using technologies like the Internet of Things (IoT). It is about leveraging insights into customer behavior, market trends, and operational efficiencies—a complete shift from the previous model based on a reactive approach to one that revolves around utilizing data for close to accurate predictions. Its benefits are enormous and include network stability, which is the foundation of a good user experience; reducing the volume of work orders and site visits, leading to a reduced cost of ownership; providing the best customer experience; reducing energy consumption; and ensuring the highest security standards.

Embarking on a data-driven transformation means leveraging a robust set of digital tools, which include automation, analytics, process mining, process discovery, machine learning (ML), and artificial intelligence (AI), to evolve the process execution from basic automation to awareness, adaptiveness, and eventually an autonomous state of orchestration. These lead to successful digital transformation for organizations of all sizes and create genuine business value and an outstanding competitive edge. These digital tools are essential to getting the most from data-driven operations.

The next evolution of data-driven operating models will need to support a wider variety of applications and use cases for consumers and businesses. Communications service providers will aim to provide configurable services with detailed agreements on functional and non-functional characteristics that require dynamic adaptation in real-time to deliver on these requirements. Concepts like “autonomous networks” and “intent” are needed to drive new propositions and automate networks to meet performance KPIs, SLAs, and business outcomes.

We see three main drivers for intent in building and operating new services. The first driver is the complexity and cost of operating 5G networks and beyond, which require a new level of automation—a level beyond even machine learning (ML) and artificial intelligence (AI). Secondly, the need to transform operations to better meet the needs of the business. Finally, the need for transparency and artificial intelligence (AI) explainability—so that we can trace back all decisions recommended and acted on by the system.

Today, Ericsson has 200 managed services contracts globally, out of which 25 have been transformed to Ericsson Operations Engine, which is a multi-vendor, multi-technology framework and the heart of our data-driven operations approach. It cuts across multiple dimensions, from processes through competence, organization, strategy, governance, data, automation, and artificial intelligence (AI).

This massive scale enables global feedback loops that we leverage to constantly evolve our processes and grow our closed-loop automation and artificial intelligence (AI) use case libraries, making it possible to handle 18.2 M work orders and 5b alarms every year with highly focused human intervention.


Figure 2: Quantitative benefits of the data-driven journey based on aggregated figures from 20 CPSs from Q1-2019 to Q4-2021.


This has a significant tangible impact on communications service providers’ operations and business outcomes. From a network performance perspective, data-driven operations reduce network unavailability by 34 percent while decreasing customer complaints by 21 percent. On the network efficiency side, the transformation led to a significant 12 percent reduction of work orders (WO) and 24 percent lesser truck rolls per node, and up to 8% reduction in energy consumption which has an important impact on CO2 emissions.

Leveraging our Managed Network Operations, we help operators transform their operations to successfully manage the increasing complexity of their networks. We achieve this by capitalizing on Ericsson’s global scale and telecom domain expertise; a proven data-driven transformation track record with outstanding results and award-winning customer references; committed service levels and predictable costs over the next 3-5 years; and the latest market artificial intelligence (AI), automation, and data insights as part of the Ericsson Operations Engine solution.

Adding people around legacy processes is not sufficient to deliver the volume and speed of change needed. A new look at data, processes, and automation is key to turning operations into data-driven ones. Transformation should not solely be focused on amending what is happening today. The real challenge lies in how to get there; it must be based on a clear vision of what the organization wants to achieve and deliver in the future. Defining this clear vision, anchored on tangible and measurable business outcomes and a solid investment plan, supported by executive sponsorship, must be the starting point.

The key to successful transformation is in the hearts and minds of the people affected. A new functional and organizational model is required to enable this digital transformation to service-centric and data-driven operations. If they embrace the vision and journey, the chances of success increase exponentially. On that basis, a smart change program is paramount and should be supported by strong and active communications and leadership involvement that engage people to propel the transformation forward.

Read more on our .com page: Data-driven operations. Does it pay off? – Ericsson

Blog originally posted on our .com page: Data is the new gold! Why data driven transformation puts you ahead of the game in Industry 4.0

Contributed by Lucky La Riccia, Head of Cloud Software & Services, Ericsson Middle East and Africa

Link to bio

AWS tees up gen AI for telecoms, Nokia shifts to Red Hat as primary infra platform

June was a hectic month for developments in network automation. Contributing editor Annie Turner rounds up some highlights.

AWS’ CodeWhisperer “coding companion” came out of beta in April. It has been trained on trillions of lines of code, so software developers can set objectives and the AI will generate the program. In June, Lightreading reported it has been shown to boost productivity by an average of 57%. Ishwar Parulkar, Chief Technologist for telecoms at AWS, is quoted in the article saying that CodeWhisperer “can be used for writing code for pretty much any kind of application”.

A photo of a host that runs AI workloadsThis is a very different proposition from the telecoms use cases talked up around Microsoft and chatGPT, which typically are sales and marketing, customer service, network management and fraud detection. This development, within such a short time of generative AI coming appearing on the radar, gives some indication of the huge breadth of the technology’s possibilities in telecoms – and the rapid ascendancy of Big Tech in the market.

In addition to all their other concerns about deploying AI – the possibility of flawed data and models producing misleading results and wrong outcomes, losing control, ethics, new regulation, data privacy and much more – they now have to mull the implications of dependency on public cloudcos for generative AI.

AWS might assuage this concern somewhat through its new, $100 million Generative AI Innovation Center. Telecoms is a target sector, along with financial services, healthcare and life sciences, automotive and manufacturing, media and entertainment, and energy.

The centre’s mission is to encourage customers around the globe create their own applications, providing access to a range of experts as well as tools like Bedrock. This is a managed service to help developers build generative AI models. A case of who engages wins for telcos?

Nokia opts for Red Hat’s infra platform

an aerial view of a grassy area with a white buildingNokia has chosen open source specialist Red Hat as its primary infrastructure platform for Nokia’s core network applications. The two say “tight integration” of Nokia’s applications with the Red Hat OpenStack Platform and Red Hat OpenShift platform enable operators to run all their workloads in a single, common layer instead of across multiple, often incompatible platforms. Importantly, the Red Hat infrastructure platform works equally well with private cloud and the hyperscalers.

Although about 350 Nokia employees will transfer to Red Hat, Nokia’s Fran Heeran said his company will continue to support its core network applications on other infrastructure platforms if that’s what customers want. He acknowledged, “We would like to see the landscape getting a little bit simpler with a little bit less choice, but at the moment it’s going in the opposite direction.” The partners hope the appeal of their end-to-end, full stack solution might help turn that around.

Rise of network automation software

brown white and blue textile

Operators’ investments in network automation software increased by more than 42% between 2020 and 2022, to $6.21 billion, according to a new report from Appledore Research. Leading Suppliers in Network Automation Software found network data management is the fastest growing segment in is a very fragmented market.

Nokia leads overall, but with just 13% market share. Huawei is hard on its heels with 12%, but they are the only two network automation software vendors with market share in double figures. The third of the ‘big three’, Ericsson, accounts for 6%.

Even those shares are under pressure though as the sector expands and smaller vendors develop software tools such as for service orchestration, AIOps, distributed cloud infrastructure, network data management, domain management and more, Appledore says.

Boost to GSMA’s API initiative

Free Woman Writing on Whiteboard Stock Photo

China Mobile, China Telecom and China Unicom have signed-up to the GSMA’s Open Gateway initiative which has a mission to provide developers with uniform, universal access to operators’ networks via open APIs. The GSMA says the initiative now has the support of 29 mobile network operators which collectively represent about 60% of mobile connections worldwide.

It was launched in February when Mats Granyrd, Director General of the GSMA, noted, “By applying the concept of interconnection for operators to the API economy developers can utilise technology once, for services such as identity, cybersecurity or billing, but with the potential to be integrated with every operator worldwide.”

Cisco to acquire Accedian

Cisco is to acquire network performance monitoring specialist Accedian, which has 75 of the globe’s top 100 telcos as customers. The value of the deal has not been disclosed but Cisco said it expects the deal to complete during the first quarter of its 2024 financial year.


Dion Joannou, CEO of Accedian, commented, “Microseconds matter to customers and customer experience, and precise, granular performance visibility is a foundational requirement for closed-loop automation, agile telco cloud environments and latency-sensitive 5G services. We look forward to bringing our critical capabilities to a wider set of solutions within Cisco’s Networking portfolio.”

Moves in the SASE market

Free Medals Tied on a Trophy Stock PhotoAccording to a new report from Dell’Oro, Cisco has been knocked off the top slot in terms of revenue by Zscaler in the secure access service edge (SASE) market. The analyst house says this is the first time Cisco has not held the top slot since it started tracking the sector in 2019. Palo Alto Networks has overtaken Broadcom (Symantec) for the third overall spot in SASE in terms of revenue.

This reflects some shifts in the market. The sector in which a single vendor offers both SD-WAN and security service edge (SSE) solutions grew 55% year-over-year in 1Q 2023, overtaking the multi-vendor SASE market, where vendors offer SD-WAN or SSE. The report says Check Point, HPE/Aruba, and Netskope have all become single-vendor SASE players. Overall SASE market revenue grew by more than 30% for the fifth consecutive quarter in 1Q 2023.

Decoding a Bottom-up Operating Model for a Successful 5G Journey

Contributed by By Don Alusha, Senior Analyst, ABI Research.

To date, Communication Service Providers (CSPs) have pursued growth by selling and upselling telephony products in the consumer domain. With 3G and 4G, CSPs create value by mapping upward on their “sustaining” cellular trajectory toward consumers that are not satisfied with the functionality that each cellular generation offers. For example, as shown in Figure 1, 2G introduced Short Messaging Service (SMS), whereas 3G introduced browsing, video, and photo sharing. And 4G introduced speed, capacity, and Internet Protocol (IP) telephony. Branding power and, by extension, value creation migrate upward on the technology improvement trajectory. By contrast, with 5G, the industry has an opportunity to introduce something above and beyond Mobile Broadband (MBB).

For example, with 5G, CSPs have the potential to offer edge services, low-latency local data and compute processing, Application Programming Interfaces (APIs), and ecosystem development. 5G is expected to enable expansion of the existing consumer value chain. But importantly, 5G redefines CSPs’ service delivery and value capture models. In other words, there is an operating model disruption. CSPs’ existing operating model changes, both in terms of the nature of requirements and the sheer requirement scope that must be managed. With 5G and software platforms, a CSP’s operating model will need to propel a series of business outcomes supported by a thorough knowledge of customer circumstances. Enhancing the predominant top-down operating model is a transition journey for CSPs. But it is one that holds potential for new growth avenues.

Consumer Operating Model

With 4G, CSPs’ operating model is both universal and uniform—integrate cellular networks to provide mass market, country- or region-specific subscriber static voice and data services. CSPs’ growth profiles revolve around technical excellence in cellular. Service logic resides within the network itself and is under CSPs’ control, producing positive feedback loops and outsize profits. A “build it and they will come” strategy is the starting point. What technology can be built is the foundation of a centrally governed approach. In that respect, CSPs capture profits from core to (subscriber) edge. It is an operating model where technology sets the (consumer) business agenda. It is an operating model where the buying party (subscriber) is a long way away from CSPs in terms of arm’s length. That is an all control, all top-down operating model that starts to be tested with 5G cloud networks and software.

Figure 1: Existing Consumer Value Chain (Source: ABI Research)


With network cloudification and 5G, the industry structure evolves toward decentralization. In contrast to 4G, 5G Network Functions (NFs) are spatially separated from one another. A case in point is local deployments of 5G User Plane Function (UPF), paving the way for CSPs to move into edge deployments and topologies. In other words, CSPs move out of the four walls of their virtual Data Center (DC) or physical DC to place networks and compute as close to their customers as they can. In a 5G era, CSPs’ cell sites, central offices, and DCs become infrastructure hubs. CSPs’ DCs grow from hundreds to potentially thousands, Virtual Machines (VMs) proliferate from hundreds to thousands, and networks increase from tens in central environments to hundreds at the “edges.” Consequently, CSPs shift from centrally hosted workloads in their DCs to a combination of central- and edge-hosted workloads in both partners’ and CSPs’ DCs.

Clearly, in a 5G era, the cellular ecosystem moves away from the “closed” and inflexible order of hierarchy toward openness and the fluidity of decentralization. And that, in turn, triggers structural changes not just in how next-generation 5G networks are designed, but also in the operating model required to commercialize those networks. These changes stand to be the pivotal axis for the emerging competitive landscape. For example, in software-centric 5G networks, there are constantly changing requirements, and there is customer- and/or service-specific connectivity. In this commercial setting, vectors like commercial focus, strategies, and operating models to execute start to be tested. Subsequently, a challenge that CSPs must contend with is on the operating model front. But the innovation potential that comes from modernizing existing cellular practices outweighs the transient challenges CSPs will have to face.

Strategize Bottom-up for a Successful 5G Journey

There is a growing demand for partners that understand customer requirements. For example, in the retail industry, for Sainsbury’s, the second largest chain of supermarkets in the United Kingdom, the requirement is not on the technology per se, but rather the business outcomes technology enables. Technology for Sainsbury’s is important as far as it enables the company to deliver on business goals. Sainsbury’s is interested in (any) technology supplier that can propel a whole series of business outcomes for it. For instance, speed of check out; how quickly they can get somebody through a register; how much shopping can Sainsbury’s digitally get inside a store; and how much data can Sainsbury’s deliver reliably to an end point (customer in store) are business outcomes it seeks to achieve. Ultimately, for Sainsbury’s, much like other enterprises and industrials, it comes back to what it wishes to achieve as a business. In other words, Sainsbury’s is on the lookout to buy solutions.

Clearly, enterprises define quality within the context of a “job to be done.” What enterprises need is the starting point. Their business outcomes set their partners’ technology agendas. In the emerging market landscape, there will be enterprise-specific, market-specific value-based engagements. Against that backdrop, CSPs will almost certainly need to learn to drive value bottom-up. In addition to continuing to excel in mass market MBB business, CSPs should adopt new business models. For example, CSPs should cater to a diverse set of application requirements, different services, and different connectivity needs. In other words, CSPs should build their growth profile starting from (enterprise) edge requirements and extending to (network and/or compute) core operations. This bottom-up, value-capture operating model equips CSPs and their peers with the readiness to intimately understand unmet individual customer requirements and respond in a targeted fashion.

5G cloud networks stand to unlock new transactions that supplement consumer volume-centered modus operandi with a bottom-up value play for discrete engagements. But the power of a bottom-up model is not enough. To monetize 5G-enabled digital services at scale, some of the existing top-down intelligence is needed, too. Learning how to operate in this hybrid top-down and the emerging bottom-up, horizontally stratified ecosystem is a journey for CSPs. Going forward, an effective and efficient operating model must contain both control and lack of control, both centralization and decentralization, and a hybrid of bottom-up plus some of the “standard” top-down intelligence. The idea is that CSPs’ operating models should flexibly fit and change in line with new and elastic market requirements as they continue their 5G journeys. Otherwise, new growth forays may hit a roadblock.


About the Author

Don Alusha is a Senior Analyst in the Telco Digitization practice at ABI Research where he provides research and analysis on service provider adoption of cloud technologies and their application in fixed and mobile networks. Pertinent research topics include Artificial Intelligence (AI) and Machine Learning (ML) technologies, Software-Defined Networking (SDN), Network Functions Virtualization (NFV), telco software, and applications.

 About ABI Research
ABI Research is a global technology intelligence firm delivering actionable research and strategic guidance to technology leaders, innovators, and decision makers around the world. Our research focuses on the transformative technologies that are dramatically reshaping industries, economies, and workforces today.

ABI Research是一家国际科技情报公司,为全球科技领袖、创新人士和决策者提供实用的市场研究和战略性指导。我们密切关注一切为各行各业、全球经济和劳动市场带来颠覆性变革的创新与技术。
For more information about ABI Research’s services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com.


FutureNet World 2023: Highlights Video

Catch up with the highlights from FutureNet World in May 2023. Hear what the CxO Speakers & Delegates thought were the key topics and talking points from the event.


FutureNet World 2023 Awards – The winners who cleared the ever-higher bar

FutureNet World was delighted to announce and congratulate the winners of its prestigious industry awards during its eponymous, award-winning and very successful event in London on 3-4 May.

And here they are…

The Operator Award for the best example of an automation deployment (for operators or operators working with vendors) was won by China Mobile in collaboration with Huawei for their digital twin solutions for autonomous networks.

Over more than three years, the operator has developed large scale automation for the network operations and is on track to achieve Level 4 automation by 2025.

It uses the digital twin network (DTN) to create a virtual mirror image of the physical network to improve risk discovery and network service quality. It provides pre-verification and simulation for iterative services that are visual and can be customised.

China Mobile and Huawei are proving the feasibility and value of DTN in simplified operations, administration and management (OAM) and to evolve automation. Two use cases to illustrate their approach.

In the first, China Mobile Henan and China Mobile Zhejiang successfully deployed digital twin technology on their core networks. When faults occur, network exceptions are detected and handled quickly. The digital twin automatically evaluates the issue, using simulation to identify bottlenecks, expand capacity and adjust parameters whereas traditional evaluation is slow and inaccurate, and can cause secondary issues.

The project uses Heteroscedastic Evolutionary Bayesian Optimisation (HEBO) which won the NeurIPS 2020 black-box optimisation competition to ensure successful core network switchover.

In the second deployment, China Mobile Guangdong and Huawei used DTN for the optical transport network (OTN) and computing force network (CFN) business scenarios. CFN is a new information infrastructure that allocates and schedules compute, storage and network resources among clouds, networks and edges, according to business needs.

This set up was seen as “a major breakthrough” in supporting multiple digital services. For an Internet of Vehicles (IoV) service, the partners created service profiles for seven car companies and 2 million vehicles, based on the twin’s data. This included establishing the IoV visualisation system, implementing quality support for core services (like vehicle information reporting, remote wake-up, rescue and upgrades). The project improved traffic operational efficiency by 12%. CFN improved the use of resources by 17%. Operations and maintenance (O&M) costs fell by 21%.

Yao Yuan, Senior AN Project Manager, China Mobile, stated on winning the Award, “In future, we will continue to explore Level 4 highly Autonomous Networks technologies and contribute more excellent practices to the industry.”


The Automation Solution Award was won by Netcracker Technology for its cloud-native Network Domain Orchestration (NDO). Automating the transport domain is important to communication service providers (CSPs) as they strive to bring agility and cost efficiency to new, dynamic services and slices. Typically they have pockets of automation isolated around vendors’ solutions, so automating transport services across multiple layers, domains and vendors has not previously been possible.

Netcracker’s NDO takes a different approach and can be applied within a single layer – for example one that has multiple IP/MPLS vendors – or where multiple vendors are deployed across multiple layers of IP/MPLS, optical and microwave infrastructure. The solution can work directly with the IP/MPLS systems or via their network management systems (NMS). For complex optical systems, the NDO works via the NMS or software-defined network controllers.

NDO works and is co-developed in DevOps mode with customers, where Open APIs are exposed to simplify integration with brownfield OSS environments. NDO enables operators to do their own configurations and become more self-sufficient.

So far the company has commercial success with 11 NDO deployments, working with BICS, Deutsche Telekom (DT), Dish, Etisalat, Globe, Segra and Swisscom. For example, DT achieved opex savings of 54 % for IP trunk provisioning and 92% opex saving for optical trunk provisioning.

Peter Arbitter is Senior VP for B2B Portfolio & Product Management at Telekom Deutschland, Deutsche Telecom’s service unit for enterprise telco clients. He stated, “We looked at the hypercompetitive and critical enterprise market and knew we wanted the most cutting-edge automation software with a cloud deployment model so that we could gain new revenue streams in multiple B2B segments.

“Through our extensive collaboration with Netcracker, we have reached an important milestone that lays the foundation for innovation and business growth.”

Ari Banerjee, SVP Strategy at Netcracker, said, “Netcracker is delighted and honoured to receive the leading automation solution award from FutureNet World. Our CSP customers have experienced impressive results by bringing full automation and agility to their transport networks with our Network Domain Orchestration solution.

“Our goal is to leverage the proven successes of these innovative CSPs to help the telco industry accelerate automation projects across all network domains and prepare for a new era of highly dynamic services and slices that will transform telco value.”


The Network Disaggregation Award for the best example of a disaggregated networking solution was won by Rakuten Symphony for its cloud-native Open RAN software in collaboration with Rakuten Mobile.

Rakuten Mobile’s nationwide 4G/5G network in Japan is the world’s first mobile network built completely using Rakuten Symphony’s cloud-native, containerised Open RAN software. The software runs 5G RAN functions as microservices in containers on a commercial, off-the-shelf (COTS) hardware platform based on O-RAN specifications and cloud-native technologies.

The disaggregated RAN hardware and software, based on Open vRAN, enables independent lifecycle management and uses DevOps and CI/CD pipelines. Disaggregating the RAN network function into different microservices means memory size can be reduced for faster start-up and restarting of functions.

Fewer onsite RAN elements and the use of COTS hardware and automation support faster site installations and maintenance. This translates to 40% less capex and up to 30% less opex compared to traditional 5G deployments, with more efficient use of resources and power. The microservice architecture allows each function to scale independently, based on demand and performance.

Vendor diversity allows the use of best-of-breed components and software in architecting and building the infrastructure for the network. The results speak for themselves.

Independent analyst firm umlaut found that Rakuten Mobile’s network in Tokyo achieved an overall score of 945 out of 1,000 in the 14 largest metropolitan areas. It also received the second-highest score in terms of coverage and speed.

Provisioning of mobile services can take as little as 3 minutes instead of 3 hours. In terms of operating efficiency, Rakuten Mobile has a low ratio of 1 engineer: 20,000 subscribers and deployment can be 4 minutes for a 5G site.

Geoff Hollingworth, CMO at Rakuten Symphony, said, “Winning the Network Disaggregation Award at the FutureNet World Awards was a proud moment for Rakuten Symphony. It’s a stage that brings together trailblazers and we’re thrilled to be part of this vibrant innovation space.

“This award shines a spotlight on the transformative impact of Open RAN and reinforces our commitment to a software-centric approach, accelerating automation and swift delivery of telecom services.”


The most innovative application of AI & Automation to enhance customer experience went to VMware for its Network Scorecard rApp (powered by VMware RAN Intelligent Controller). This AI-driven application monitors a network’s market performance to enhance customer experience.

Operators that deploy Open RAN face the complex task of assessing the quality of their network across multiple markets. The networks are designed with different structures and forms, have various user traffic patterns and equipment from multiple vendors.

To succeed, operators must continuously monitor each market to detect performance issues before they impact customers. Without AI, this is an impossible task; traditional methods also ignore contextual factors that can cause unexpected network behaviour.

VMware Network Scorecard rApp, powered by the VMware Centralized RAN Intelligent Controller or RIC (that is, a non-real time RIC implementation) solves this time, resources and performance problem. It is fully automated and uses an AI-based analytical framework.

The Network Scorecard application ingests data from all sectors in all the markets it controls, adding context to the measured values, such as channel quality indicator (CQI). It assigns a ‘score’ to each market, based on how actual performance compares to the AI-derived benchmark. The insights generated from the comparison help the CSP to make network changes to remedy issues.

VMware Network Scorecard was built using the VMware RIC software development kit (SDK) to help onboarding by CSPs and is available to third-party developers via the RIC Partner Program. This is designed  to accelerate the development of xApps and  rApps. Various companies have brought their applications to market via the Partner Program, fast-tracking the latest research from universities and other bodies into commercial-ready solutions.

Stephen Spellicy, Vice President Service Provider Marketing, Enablement and Business Development, VMware, said, “I’m delighted that the judges recognised the VMware Network Scorecard rAPP in association with the VMware RIC as the winner for the Most Innovative Application of AI and Automation to enhance customer experience. Simplifying the network to produce clear and measurable benchmarks is a key operational need and assists operators in meeting their customer experience KPIs as we move towards an Open RAN architecture.

“VMware has always been an ecosystem player and, although the Network Scorecard is a VMware-developed product, I believe the judges recognised the lengths to which VMware goes to embrace the entire ecosystem.”


The Orchestration Award for the most innovative automated service orchestration solution was won by Inmanta for its Mobile Private Networks Orchestrator (MPNO) Solution. Inmanta’s patented service orchestration technology is the brainchild of three PhDs in computer science and the result of more than 15 years’ R&D. They says its key differentiator is being a purpose built, intent-based service orchestrator that is multi-domain by design.

On winning the award, Stefan Walraven, Co-founder & CEO of Inmanta, stated, “FutureNet World is the most prominent event for network automation, orchestration and AI in the telecom industry.

“Being judged by industry experts validates our dedication to pushing the boundaries of orchestration and reinforces our position as a trailblazer in the field. Receiving the award is a great recognition for the innovative work we do at Inmanta, especially winning in the face of all the other incredible nominees…who have made their mark in the industry.”

The MPNO allows multi-vendor private 5G networks to be deployed in less than 10 minutes, giving service providers the choice and flexibility to scale and create new revenue streams from the enterprise market.

The company claims MPNO is the first comprehensive orchestration solution in the market that deploys a fully automated end-to-end private network involving multiple vendors across edge, backhaul/transport, RAN, data centres and cloud, including setting up the data networks (that is, network slices) and configuring the firewalls.

Inmanta cited a customer case study whereby Citymesh uses the MPNO to deploy fully operational, private mobile networks in under 10 minutes commercially. Citymesh is a wireless B2B telecom operator, specialising in the design, fabrication, installation, deployment and management of wireless network solutions and products for the on and offshore critical operations and applications based on 4G/5G spectrum.

Citymesh is able to orchestrate and manage the lifecycle of its mobile private networks centrally and support frequent upgrades to its Athonet 5G Core, seamlessly and 100% unattended. Self-healing ensures the integrity and resilience of the private mobile networks, reducing what can be expensive operational costs in cases of failures, for example in off-shore networks.

Any new deployment will have automated testing, ensuring Citymesh’s customers have an operational network that complies with their SLAs. The end result is that Citymesh can scale hundreds of private networks with the same operations team.


The AIOps Award for the best operations solution incorporating AI functionality was presented to Nokia for its Homeview Solution in collaboration with BT.

BT manages nearly 10 million multi-vendor endpoints within UK homes including routers and set-top boxes. Delivering reliable, high-performance broadband to a big subscriber base was putting pressure on opex and resulted in long average call-handling times for customers phoning call centres with problems. Challenges in identifying problems and their resolution meant a high percentage of calls culminated in truck rolls to customers’ premises.

BT found that 60% of reported problems originated in the home Wi-Fi connectivity which is subject to all kinds of environmental issues, from impenetrable walls to radio interference.

BT wanted an AIOps solution to provide real-time observability, actionable recommendations and automated workflows to reduce the cost and complexity of fixed broadband troubleshooting, while providing better customer experience.

Nokia and BT developed HomeView which applies Bell Labs AI/ML predictive models to raw telemetry data from home devices to uncover correlations and causality related to current and potential network issues. BT’s broadband operations teams and more than 6,000 customer care agents are using the HomeView AIOps solution. So far it has saved more than £1 million annually through fewer truck-rolls and a further £1 million a year from shorter calls to customer care and proactive troubleshooting.

On average, BT now receives 260,000 fewer troubleshooting calls annually – the equivalent of 18,072 working days and, via the Smart Assistant, achieved a 10% improvement in first contact resolution.

Nokia and BT are implementing more than 30 ML- and analytics-based diagnostic capabilities this year to improve proactive identification and resolution of potential issues in the broadband network before they impact services. Nokia is also helping BT position itself to move up the value chain and address new revenue streams from future managed smart home opportunities.

“BT and Nokia partnered to revolutionise BT’s fixed broadband operations and customer care. Their collaborative effort produced HomeView, an AI/ML-powered solution that enhances the customer experience for BT subscribers and boosts operational efficiency with over 6,000 customer care agents benefiting from this innovation,” said Hamdy Farid, Senior Vice President, Business Applications at Nokia.

He added, “This award solidifies Nokia’s industry leadership in analytics, customer care automation, and carrier-grade device management, demonstrating its ability to drive tangible business results through AIOps for leading operators worldwide.”


The Network Sustainability Award for the best intelligent automation solution for network sustainability and energy efficiency was won by Ericsson and its Predictive Cell Energy Management (PCEM) solution. It is designed to reduce energy consumption by up to 8% while maintaining network quality and customer experience. As PCEM has a cloud-native architecture, it is also instantly scalable.

Over the last 18 months, Ericsson has run 20 trials of PCEM and customer deployments involving 6 million cells. Through supporting 16 billion predictions and automated activities in a year, it saved $60 million on energy on top of existing RAN energy-saving features and reduced CO2 by 200,000 tons.

PCEM´s Intelligence & Recommendation Engine provides granular, real-time data on energy consumption and performance for individual cells. This allows operators to define data-driven protocols, powered by multiple AI – machine learning – algorithms that allow operators to respond dynamically to hourly, daily and seasonal traffic changes, with very high accuracy, on a per cell basis.

In parallel, the solution’s Automation Engine implements the best energy-saving actions for a specific site at a particular moment using closed loop automation.

This approach contrasts with most energy saving applications on the RAN which tend to use the RAN power-saving features available with each different type of radios. Although they allow the radios to be activated and deactivated instantly, based on real-time traffic changes, they can only be configured based on certain traffic configurations and thresholds (like power use).

They do not have dynamic management protocols or tools to address different traffic (urban, sub-urban, rural etc.) and network configuration profiles. Hence operators tend to use blanket configurations at a network level and the power saving features only work on their designated technology (2G, 3G, 4G, 5G).

Sam Keys-Toyer, Head of Business & Portfolio Development for Managed Network Services, said, “We are incredibly proud to see our efforts are recognised outside the company on such an important topic not only for our customers, but for the planet.

“We are dedicated to creating a more sustainable future and this recognition is true testimony to how the Ericsson Operations Engine continues to transform network operations to be data driven, with a strong focus on reducing energy consumption for our CSP customers, while maintaining optimal network performance”.


The Technology Leader Award – Outstanding contribution throughout their career was won by Enrique Blanco, Chief Technology & Information Officer, Telefónica.

Watch the moment Enrique Blanco was awarded for an outstanding contribution throughout his career…


Congratulations again to all our winners and to everyone who submitted an entry. This was a truly outstanding field.


Presentation: Data transformation: The pathway to becoming a data driven company

Watch On-Demand. Broadcast live at FutureNet World on the 4th of May 2023.

  • Antonietta Mastroianni, Chief Digital & IT Officer, Proximus