On this episode of the Six Five Podcast – The 5G Factor, host Ron Westfall assesses why T-Mobile’s Capital Market Day energized 5G ecosystem interest in AI RAN, how T-Mobile’s alliance with NVIDIA, Ericsson, and Nokia can produce an AI RAN “Fantastic Four,” a snapshot of the AI RAN market segment including NVIDIA’s competitive position, and why he agrees with Orange that Open RAN can prove its green credentials.
The assessment covers:
- How T-Mobile shrewdly leveraged its Capital Market Day event to unveil its new AI-RAN alliance with NVIDIA, Ericsson, and Nokia.
- Why T-Mobile and its key AI RAN partners, NVIDIA, Ericsson, and Nokia, are taking advantage of increased mobile ecosystem interest in AI RAN that is fueled heavily by the accelerating integration of AI throughout RAN portfolio development and deployments.
- NVIDIA Aerial AI Radio Frameworks include PyTorch- and TensorFlow-based software libraries to develop and train models for improving spectral efficiency and adding new capabilities to 5G and 6G radio signal processing.
- Why the Orange Group is warranted in its confidence that O-RAN-compliant radio units can achieve energy efficiencies comparable to traditional RUs.
Learn more about the Six Five Podcast – The 5G Factor at The Futurum Group.
Listen to the audio here:
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Transcript:
Ron Westfall: Hello, and welcome, everyone, to The 5G Factor. I’m Ron Westfall, Research Director here at The Futurum Group. And today, I am focusing on the major 5G ecosystem developments that have caught my eye. And this includes T-Mobile energizing 5G ecosystem interests and AI-RAN technology. Also, as snapshot of the AI-RAN market segment, including NVIDIA’s competitive position. And closely related, what’s going on with Open RAN, and can Open RAN prove its green credentials. So with that, there is a lot on tap, and let’s dive right in.
Well first of all, I believe T-Mobile shrewdly leveraged its Capital Market Day event on September 18th to unveil its new AI-RAN Alliance initiatives with NVIDIA, Ericsson and Nokia. Now, the initiative is definitely timed as AI-RAN is poised to substantially enhance customer real-world network experience, meet the overgrowing demand for higher speeds, reduce latency naturally, and increase reliability, essential for the latest gaming, video, social media, and augmented reality applications. That’s right, AR. And I’m glad that AR is called out, because in my conversations, I’m seeing uptick in 5G supporting AR capabilities. And so the question is what’s the use case? What’s the context? What we’re seeing is that construction sites and in any environment that requires drawings or the ability to provide a 3D viewpoint of an existing environment, well there it is, AR is critical. And that includes many settings where only 5G can provide a real-time connectivity capability. And so, this is, I think, something that we’ll see more of because AR initially was touted as a huge application that 5G would be supporting. It dialed back in terms of the actual use cases and capabilities. But now I’m seeing that AR is going to be integral to why 5G connectivity will become more, not only widely implemented, but also monetized, quite simply. And so this is something I think that T-Mobile with its announcements at its Capital Day event will, I think, definitely raise the interest in profile.
And so, to step back, what are the key aspects here about AI-RAN, and why would T-Mobile, along with NVIDIA, Ericsson, Nokia, pick this time to discuss what is going on? Well, first of all, I believe AI-RAN technology can achieve the harnessing of billions of data points to create algorithms that optimize network adjustments for peak performance and predict real time capacity needs where customers require it most. Now, there’s been progress in this area, but it hasn’t really been a true real time dynamic capability. And so, what is the technology? It has to enable automation, quite clearly. And AI is clearly the underlying technology, I believe, along with its cousin, machine learning, that can provide this ability to adjust the network requirements according to real world and real time requirements, without compromising security, without trade-offs and performance, and say, other parts of the network and so forth. And that’s really, I think, a dramatic breakthrough that we’re on the precipice of seeing.
And so, in addition to that, I anticipate that AI can enhance RAN performance and automate operations as well as, quite simply, elevate mobile network infrastructure performance, enabling it to run third party AI application workloads that the network edge, well, simultaneously. And so, this is a lot. It’s a lot being packed in. But that’s, I think, how AI can make a significant difference that we haven’t seen yet in terms of 5G network capabilities, let alone overall mobile and wireless networking capabilities. And this is also going to be important for related technology such as WiFi. I think you’ll see many environments where there’s a preference to use WiFi, say, at a central site, but we definitely need to use a 5G implementation or a private 5G implementation to address wide area network environments.
And so that means there’s be more blending of the private 5G, 5G and a WiFi worlds. And what’s going to be the technology that could underline how this can come together best? Well AI, I think, is the answer. At least AI is going to play a central role in this. Now also AI-RAN specifically is being developed alongside other advanced 5G features, in collaboration with T-Mobile and its partners. Now, the new alliance, I guess you can call it, is prioritizing that AI-RAN concepts will be developed in an open and containerized fashion along the same principles as Open RAN. And so, there’s some skepticism, like okay, is T-Mobile tossing a satin to the Open RAN ring? I believe because they’ve been not using Open RAN, I believe this is something that needs a level set understanding. We saw that AT&T, when it announced that it was using Ericsson as its prime lead integrator for open RAN implementation, that’s basically how almost any top tier operator is going to unfold its Open RAN implementation when they believe it’s ready for them. And what that means is that an Ericsson or an Nokia will probably play the lead integrator role, and then bring on other partners as required. That would certainly include selecting the chip set of vendors that they deem most well suited for the specific unique needs of the operator, but also bringing in an alternative radio supplier like Fujitsu and when it came to the AT&T and Ericsson collaboration, and as well as other third parties such as Amdocs when it comes to some of the BSS or OSS capabilities.
So it’s really going to be a case by case basis where the operator is going to select a lead integrator. And working together, they’ll decide who is best suited for the initial deployment of Open RAN. And then, after it’s been battle tested, then we’ll see more diversification of suppliers and so forth. So it really is an exercise in patience. This is not unique to Open RAN, we’ve seen this with other technologies. But I think it’s really good news overall that AI-RAN can actually, at the end of the day, be a good friend to Open RAN. And as a result, really invigorate the Open RAN implementations out there. There are still less than 10% of the overall RAN implementations out there. So that is, I think, going to trend toward the advantage of Open RAN, the fact that AI-RAN will now become more, I think, prioritized in the planning of the major operators. And certainly T-Mobile is proving that. And to reiterate, I think AI-RAN stands out as a breakout technology because it can significantly enhance the existing Open RAN architecture, but also, it’s allowing the collaboration that needed to demonstrate that AI-RAN can not only fulfill the potential of Open RAN, but also quite simply surpass its expectations.
And so this is exciting. I think this is a collaboration that will not only earmark how AI-RAN technology can be truly innovative, but also impact the other parts of the network that includes 5G core capabilities, 5G advanced implementations, and ultimately, 6G itself, which I still think it’s a little premature to talk about in terms of its practical implementation. But let’s first of all get 5G standalone more widely deployed, see how 5G advanced innovations make an impact. And then I think a year or two from now, we can talk more pragmatically about okay, 6G. But yes, on the R&D side, 6G is certainly has to be a part of the planning there. Now, what T-Mobile is doing with NVIDIA, Ericsson and Nokia is taking advantage of increased mobile ecosystem interests in AI-RAN itself. It debuted basically at Mobile World Congress in Barcelona at the beginning of the year and has since, I think, garnered a lot of interest because we’ve seen fundamentally a stalling, if you will, of 5G deployments overall. And a lot of it’s associated with the RAN. And the fact that Open RAN hasn’t really taken off, it’s really in the eye of the beholder as we solve with the AT&T, the Ericsson partnership.
But I think that is going to basically recede in terms of perception. It’s like, okay, Open RAN will increasingly become just that, integral to the planning of the operators, and that there’s a lot of, quite simply, ecosystem support behind it, not just from the operators who are getting past, okay, we want to support Open RAN in principle, but how can we implement it in reality? That I think is the challenge that’s ongoing right now, but also, have national governments and other imperatives as to why Open RAN will become more important as less reliance on supply chain surprises, or less risk, I should say, of supply chain surprises coming out specifically from the Asia Pacific region. And that’s something that Open RAN can play a role in. We see players like Mavenir, for example, being able to step up and show that Open RAN can come from an independent supplier. Also, I think what’s important here is that you have wider deployment of 5G sensors, which means that the mobile network operators will have to improve their RAN and overall mobile network efficiencies, as I touched on, as well as augment overall network edge intelligence. So it’s not just about, okay, a better experience for consumers, but then also certainly businesses. But the IOT component, i.e. I think IOT is going to play a major role in how mobile operators can sell 5G, diversify the revenue streams and so forth. And that includes 5G sensors for the AI or the AR applications I touched on, but also things such as intelligent video monitoring as well as advanced gaming capabilities we’ve heard about, but actually making it happen.
Moreover, I see that the suppliers across the mobile ecosystem chain will increasingly integrate AI-enabled RAN platforms to basically keep an eye on decreasing RAN power consumption. I’m going to touch on this more, as well as costs. And that can also boost what are increasingly important digital twin outcomes. And that’s part of the AR piece. But digital twins are also important for many environments that is having a simulation of a real-world environment that can allow the decision makers to make better decisions quite simply about what is going on. And I think a good analogy, and I’ve invoked it before, is what we do with Google Maps as well as GPS, is giving a real-world simulation of what’s going on with the traffic out there, and how you can get from one destination to the other in an optimized fashion. Well, the same thing with construction sites. The same thing basically with any R&D environment that would like an accelerated output of how can we better design, say, the mobile network itself, but also smart buildings, smart cities. There’s just a whole host of use case scenarios where 5G can play an integral role using AI as a difference maker. Also, I think that it’s important to note that the AI-RAN cloud-based multi-purpose network has the potential support, not just the traditional Telco workloads, but also Core RAN, and also AI workloads together. And that it can be better enabled through what is being labeled as AI as a service. So AI as a service, there’s a long line of as-a-service capabilities out there. I think, well, quite simply, have more prominence amongst the as-a-service capabilities out there, such as infrastructure as a service, software as a service, platform as a service.
And so this is good news. This is good news for mobile network operators, but certainly also for businesses, and as well as increasing competition across the entire mobile ecosystem. Now, the next steps, let’s say, we’re seeing enhanced capacity, better energy of efficiency and improved resiliency. That means that new Gen AI applications, along with the traditional workloads such as voice, video and data, have the capability to make better contextual decisions about how to best utilize network performance parameters. And also, again, it’s about cost savings. And so, when these capabilities are firing in all cylinders, that just quite simply improves the total cost of ownership metrics for the mobile network operators, and thus, spur more investment in terms of how can we best use AI to improve RAN network performance, but from there, across the entire mobile network. And so, moving on to the next theme, the second major theme, it’s again about AI-RAN. But let’s drill down more into what are these AI-RAN capabilities, specifically when it’s related to NVIDIA AI aerial technology, which was certainly featured in the announcements by T-Mobile related to AI-RAN. Now, what we’re seeing is that telecommunication providers are evolving beyond their traditional services. They certainly, it’s a strategic aim by using AI computing capabilities. Now, this means how can that be translated into these improved outcomes that we talked about? Well, this transformation requires the optimization of wireless networks to meet demands of generative AI across mobile devices as well as basically any device out there that requires it, robots, autonomous vehicles, smart technologies, and so forth.
And so, I think it’s important to note, what are the capabilities that the NVIDIA AI aerial platform is supporting? Well, first of all, NVIDIA Aerial CUDA Accelerated includes a software libraries that enable partners to develop and deploy high-performance, virtualized RAN workloads on NVIDIA accelerated compute platforms. Okay, that’s pretty, would say self-evident. But what’s also important are the following two out in second. NVIDIA AI aerial radio framework includes PyTorch and TensorFlow-based software libraries to develop and train models for improving spectral efficiency and adding new capabilities to 5G, and ultimately 6G radio signal processing. And this includes NVIDIA Sionna, a link level simulator that provides development and training of neural network-based 5G and 5G radio algorithms. So this is ambitious. This is really NVIDIA stepping up and saying, all right, they’re all alternatives to how virtual RAN and Open-RAN implementations are being done today. And that is naturally a direct challenge to Intel and it’s X86 CPU approach. Now that does not by any means mean game over. What it means is that okay, there are some competitive alternatives out there that could spur Intel to really step up its X86 game, for example, and come up with ways to show that, okay, this is an approach that will be, if not a key part, but one that can answer some of the things that NVIDIA is bringing to the. And third, NVIDIA Aerial Omniverse Digital Twin, Digital Twins once again, or AODT is a system-level network digital twin development platform that can enable the physically accurate simulation of wireless systems. I already pointed out this. And that actually, to provide more detail, that comes from a single base station to a comprehensive network with a larger number of base stations covering an entire city.
So in other words, the networks can be smarter. We can simulate not just the base station level, but entire cities, for example, which would be crucial for a mobile network operator. And then ultimately, perhaps the end-end network itself. And so, it’s doing this by incorporating software-defined RAN, CUDA-accelerated capabilities along with the user equipment simulators and realistic terrain and object properties of the physical world. So this is moving along. And this is coming closer to a mobile network to you. Now, I think what’s also important to note here is that NVIDIA AI Aerial is a suite of accelerated computing software and hardware that’s designed to really accelerate the simulation training deployment of AI-RAN technologies. So that’s, to reiterate, what is the objective here. And pivoting off of that, the platform can become a critical foundation to allow network optimization, at scale, to serve the demands of a host of new application services, capabilities. And this could ultimately provide savings and TCO, but also open telecom operators to revenue opportunities across the enterprise space, complementing existing consumer services. And I think it’s also important to note that it’s fulfilling really both the general purpose and virtualization boxes. And while NVIDIA thinks AI itself can help to reduce energy consumption, GPUs, as we see in data centers that are using GPU clusters to do heavy lifting, AI training, quite simply require a lot of energy. And as a result, they’re power hungry. And that includes in comparison to CPUs and other accelerators. And that is going back to, okay, NVIDIA versus Intel when it comes to the future of Open RAN, the future of virtual RAN.
And this could be a decisive factor, actually, for Intel if it can show, okay, energy efficiency can actually be better attained through a CPU centric approach. However, let’s let the competition commence. As we see with edge competing, which involves hosting applications closer to mobile sites, rather than those large data centers, there’s been a topic of discussion as to how this can be applied to virtual RAN. And while progress has been, I would say limited, it’s, I think, indicative that when you’re seeing more neutral host implementations as well as other implementations at the edge, that both NVIDIA, Intel are stepping up to demonstrate this is something that the mobile ecosystem can take advantage of. And so, I think it’s important to note that when it comes to the virtual RAN market, there has been a lack of an ARM or X86 based alternative to Intel, but I think we’re going to see more alternatives coming to the forefront, and that includes an AI centric or GPU centric approach by NVIDIA. Now, I think it’s also important to note that when it comes to the NVIDIA Aerial Omniverse Digital Twin applications, we’re already seeing, I would say, partnership support. Keysight, for example, is using the technology for its testing and simulation systems, while we’re seeing partners such as DeepSig, Northeastern University and Samsung collaborating on 6G research using NVIDIA aerial AI radio frameworks. So this is showing that that vital ecosystem support is becoming more real.
Also, I am seeing that the cloud stack software provider such as Aarna Networks, Canonical, Red Hat and Wind River, and as well as network stack providers such as Arrcus are providing that support for network and server capabilities to enhance capabilities that are being offered by Dell, HPE, as well as Supermicro. And these are all key partners for NVIDIA in this segment, at least using NVIDIA AI aerial technology solutions. And it doesn’t stop there. There’s also Vapor IO. And system integrators like Worldwide Technology also exploring how can we use the AI proving ground of NVIDIA, but also ultimately the T-Mobile Testing Center to figure out how we can make AI work better for RAN implementations. And as a result, the overall mobile network. And I think it’s also important, rounding out here, to talk about the energy efficiency and sustainability aspects. Now the hope is that GPU energy efficiency using AI can be improved at the edge. And it’s different again from data center environments. And that includes a CPU technology, whether it’s X86 based or using arm based implementations. The bottom line is the energy efficiency has to be there in order for the mobile network operators to offer a more compelling service, but also for them to meet their own in-house sustainability goals. And I don’t think that’s off the table at all. It’s definitely something that the mobile network operators are keeping close eye on as they’re looking at ways to innovate their overall mobile network implementations.
And with that in mind, I thought it was interesting that Orange Group is confident that O-RAN compliant radio units can achieve energy efficiencies comparable to traditional RUs. And so this is important. This has been a bit of a debating point. Can Open RAN actually at least match or exceed the energy efficiencies that we’re seeing with ongoing RU implementations? And this could be a real game decision breaker, that is, if Open RAN cannot improve on traditional RUs in this regard, then it could quite simply continue spinning its wheels in terms of market presence. So what we’re seeing is that when it comes to cloud RAN ecosystem, which basically is, I would say a subset of the overall Open RAN realm, it’s important that it can support virtualized baseband units, as well as distributed units, and as well as centralized units, and operating on commercial off-the-shelf hardware with accelerators that deliver, again, those energy efficiency gains. Now, so why is Orange confident about this? Well, it’s really taking advantage of these new chipsets that are coming down. And that cloud RAN specifically can match from 2025 onwards that is, the energy efficiency performance of those traditional RANs, and high-capacity urban scenarios. So this is not going to be an overnight sensation, but again, when it comes to those dense, urban settings, we can see Open RAN again exceeding what traditional RAN could do in this particular area. And what else is contributing to this? Well, using massive MIMO technology, running again on those generic hardware platforms, combined again with those purpose-built accelerators.
Now I believe there’s been progress, not only with the chipsets and accelerators, but I think Orange brings out a very important point also with the dimensioning part. And this is again where AI is helping play a role. And with the newer chipsets that are coming out or have come out, it should, as a result, be able to provide highest-capacity scenarios with the mix of FDD bands and TDD bands in massive MIMO in a single server. So that’s bringing a lot of factors together, but I think that’s going to be the bottom line, can an operator like Orange use a single server to combine these well-established bands on the FDD and TDD side using massive MIMO to attain these energy efficiency objectives? And that sure is looking like it. Orange would not be talking about it if not otherwise. Also, I think it’s interesting to note that chipset developments from various suppliers, and also noting RAN advances made by, again, NVIDIA that Orange is expecting performance crossover between dedicated and generic hardware will happen sometime next year, or at least no later than 2026. So that’s really putting a lot on the line. It’s saying, “We’re putting our money where our mouth is.” Aren’t just saying, “Okay, we believe that the NVIDIA proposition is going to help drive this.” And that’s tying back again to why the T-Mobile announcement on the AI-RAN side itself is so momentous. And also, spotlighting that NVIDIA, Ericsson and Nokia are all on board. And this is just exciting. This is just going to be, I think, great news for making the RAN market segment itself more interesting, that is more Open RAN implementations, or at least accelerating them, and also just intensifying the competition.
And with that, I would like to say thank you all for joining The 5G Factor. Again, please bookmark The 5G Factor. It’s on The Futurum Group website. And always appreciate folks taking time to listen to my thoughts on what is going on. That is so exciting, and I’m looking forward to providing an episode next week as well. And with that, thank you everyone. Have a great 5G and AI-RAN day.
Other insights from The Futurum Group:
5G Factor: AI RAN and Telco AI Rising
T-Mobile Reports Stellar Q2 2024 Earnings, Raises Guidance for the Year
DTW24: Dell and Ericsson Boost Joint Goal to Spur Telco Cloud Journeys
Author Information
Ron is an experienced, customer-focused research expert and analyst, with over 20 years of experience in the digital and IT transformation markets, working with businesses to drive consistent revenue and sales growth.
He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including a wide range of topics across software and services, infrastructure, 5G communications, Internet of Things (IoT), Artificial Intelligence (AI), analytics, security, cloud computing, revenue management, and regulatory issues.
Prior to his work with The Futurum Group, Ron worked with GlobalData Technology creating syndicated and custom research across a wide variety of technical fields. His work with Current Analysis focused on the broadband and service provider infrastructure markets.
Ron holds a Master of Arts in Public Policy from University of Nevada — Las Vegas and a Bachelor of Arts in political science/government from William and Mary.
