T-Mobile Capital Market Day, AI-RAN and Open RAN Rising – 5G Factor – EP72

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 in AI ran technology.

Also a 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, uh, tap and let's dive right in. Well, first of all, I believe T-Mobile's 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, uh, construction sites and in any environment that requires, uh, drawings or the ability to provide a 3D viewpoint of an existing environment, well, there it is, AR is uh, critical and that includes, uh, many settings where only 5G can provide a real time connectivity, uh, 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 kind of, uh, dialed back in terms of, you know, the actual, uh, use cases and capabilities.

But now I'm seeing that AR is going to be integral to why 5G connectivity will become more, uh, not only widely, uh, implemented, but also monetized quite simply. And so this is something I think that T-Mobile with its, uh, announcements at the capital, uh, at its, uh, capital Day event will, I think definitely raise, uh, 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 Eric Sinopia pick this time to discuss, you know, what is going on?

Well, first of all, I believe AI ran technology can achieve the hardest thing 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, uh, cause of machine learning that can provide this, you know, ability to adjust, you know, uh, the network requirements according to real world and real time requirements without compromising security, without trade offs in performance and say other parts of the network and so forth. That's really, I think, a, a dramatic breakthrough that we're on the, uh, the, uh, precipice of c And so in addition to that, I can 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 at 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've haven't seen yet in terms of 5G network capabilities, let alone overall mobile and wireless networking capabilities. And this is also gonna be important for, uh, related technology such as, you know, wifi, I think you'll see many environments where, uh, 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, you know, wide area network environments. And so that means there's be more blending, uh, the private 5G 5G and uh, wifi worlds and what's going to be, you know, the technology that could underline, you know, how this can come together best.

Well, AI, I think is the answer, at least AI is gonna 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, uh, the new, uh, 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, you know, tossing a sat into the open ran ring?

I believe, uh, because, you know, they've been not using Open ran and I believe, uh, this is something that, uh, needs a, uh, level set understanding. We saw that at and 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 that.

And what that means is that an EID or a Nokia will probably play the lead integrator role and then bring on other partners as required. That would certainly include, you know, selecting the chip set of vendors that they deem most well suited for, you know, the specific unique needs of the operator, but also bringing in, you know, an alternative radio supplier like Fujitsu. And when it came to the at and t and Ericsson, uh, collaboration and as, as well as, you know, other third parties such as, you know, and o when it comes to, you know, some of the BSS or OSS capabilities.

So it's really gonna be a case by case basis where the, uh, 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, you know, after you know, it's been battle tested, then we'll see more diversification of suppliers and so forth. So it really is an exercise in patients.

This is not unique to Open Brand. 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, uh, really invigorate the open RAN implementations out there. There's still less than 10% of the overall RAN implementations out there.

So that is, I think, going its trend toward the advantage of Open ran. The fact that AI ran will now become more, I think, uh, prioritized in the planning of, you know, 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, uh, to demonstrate that AI ran could not only fulfill the potential of VPA ran, but also quite simply surpass its expectations.

And so this is exciting. I I think this is, uh, a collaboration that will not only earmark how a RAN technology can be truly innovative, but also impact the other parts of the network that includes, you know, 5G core capabilities, 5G advanced implementations, and ultimately six G 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, six G. But yes, on the RD side, six G is certainly has to be a part of the planning there. Now, what T-Mobile's doing with Nvidia Ericsson and OIA is taking advantage of increased mobile ecosystem interests in AI ran itself, the debuted basically at Mobile World Congress and 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, you know, 5G deployments overall.

A lot of it's associated with the RAN and the fact that open ran has really taken off. It's really in the eye, the beholder as we saw with the at and t uh, Ericsson, uh, partnership. But I think that is going to, uh, basically recede in terms of, you know, perception.

It's like, okay, open ran will increasingly become just that, uh, 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 random principle, but how can we implement it in reality? That I think is, you know, the challenge that's ongoing right now. We also have national governments and, you know, other, uh, you know, imperatives as to why open ran will become more important.

There's less reliance on, you know, supply chain surprises, or less risk, I should say, of supply chain surprises, you know, coming out specifically, uh, from the Asia Pacific region, and that's something that Open ran, uh, can play a role in. We see players like Avenir, 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 we 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, IEI think IO OT is going to play a major role in how mobile operators can sell 5G, you know, 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, uh, such as intelligent video monitoring, uh, 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, uh, chain will increasingly integrate AI enabled RAN platforms to basically keep an eye on decreasing ran power consumption. I'm gonna touch on this more as well as costs, and that can also boost what are, uh, 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, uh, uh, decisions quite simply about what is going on.

And I think a good analogy, and I've uh, invoked it before is what we do with, uh, Google Maps as well as GPS is giving a, a real world simulation of what's going on with the traffic out there and how you can get, get from one destination to the other in an optimized fashion. Well, the same thing, uh, with, you know, construction sites, the same thing, uh, basically if any r and d environment that would like, you know, an accelerated output of how can we better design, say, you know, the mobile network itself, but also, you know, smart buildings, uh, smart cities, you know, 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 multipurpose 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, uh, better enabled through what is, uh, being labeled as AI as a service.

So AI as a service, uh, you know, there's a long line of, as a service capabilities out there, I think will, uh, quite simply have more prominence and, um, you know, 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, you know, for mobile network operators, but certainly also for businesses and as well as, you know, increasing competition across the entire mobile ecosystem. Now, the next steps, let's say, you know, we're seeing enhanced capacity, better en energy efficiency and improved resiliency.

That means that new Git AI applications along with the traditional, uh, workloads such as voice, video and data, have the capability to make better contextual decisions about how to best utilize network, uh, performance, uh, parameters. And also, uh, 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, I think, uh, 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, uh, was certainly featured in the announcements, uh, by T-Mobile related to AI ran. Now what we're seeing is that telecommunication providers are evolving beyond, you know, 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, uh, requires the optimization of wireless networks to meet demands of generative AI across mobile devices, as well as, you know, basically any device out there that requires it, robots, uh, 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, uh, supporting?

Well, first of all, uh, Nvidia aerial coda accelerate includes a software libraries that enable partners, uh, to develop and deploy high performance virtualized ran workloads on NVIDIA accelerated compute platforms. Okay? That's, you know, uh, pretty, I would say self-evident, but what's also important are the following two out in second.

And Nvidia ai, aerial radio framework includes PyTorch, I tensor, flow based software libraries, developed and trained models for improving spectral efficiency and adding new capabilities to 5G and ultimately six G radio signal processing. And this includes Nvidia ana, a link level simulator that provides development and training of neural network-based 5G and six G radio algorithms. So this is ambitious.

This is really Nvidia stepping up and saying, all right, there are all alternatives to how virtual ran and open ran implementations are being done to today. And that is naturally a direct challenge to Intel, and its X 86 CPU approach. Now, that's, that's not by any means, mean game over.

What it means is that, okay, there are some competitive alternatives out there, uh, that could spurt intel to really step up. Its X 86 game, for example, and come up with ways to show that, okay, this is an approach that will be of, if not a key part, but one that can answer, you know, some of the things that NVIDIA is bringing to the table. And third, Nvidia aerial omniverse, digital twin, digital twin twins, again, or A ODT is a system level network, digital twin development platform that can enable, uh, uh, the physically accurate simulation of wireless systems.

I already pointed out this and that actually to provide more to 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, you know, the, uh, base station level, but entire, you know, cities, uh, for example, which would be crucial for a mobile network operator, and then ultimately perhaps the end-to-end network itself.

And so it's doing this by incorporating software defined ran, uh, could accelerated, uh, 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, you know, to reiterate what is the objective here. And, but pivoting off of that, the platform can become a critical foundation to allow network optimization at scale to serve the, the demands of a host of new application services capabilities. And this could ultimately provide savings and TCO, but also open tele telecom operators to revenue opportunities across, uh, the enterprise space complementing existing consumer services.

And I think it's also important to note that, uh, 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 seeing, uh, you know, data centers that are using GPU clusters to do heavy lifting, uh, 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, uh, actually be better attained through A-A-C-P-U centric approach. However, let's, you know, let the competition commits.

Uh, as we've seen with Edge competing, which involves, you know, hosting applications closer to mobile sites rather than, you know, those large data centers, there's, uh, been a topic of discussion as to how this can be applied, uh, to virtual ran. And while progress has been, I would say limited, it's, I think indicative that when you're seeing more neutral hosts, uh, implementations as well as other implementations at the edge, that both Nvidia Intel are stepping up to demonstrate this is something that, uh, the mobile ecosystem can take advantage of. And so I think it's all important to note that when it comes to the virtual ran, uh, market, there has been a lack of an ARM or X 86 based alternative to Intel, but I think we're gonna see, uh, more alternatives coming to the forefront, and that includes an, uh, AI centric, uh, or GPU centric approach by Nvidia.

Now, I think it's also important to note that, uh, when it comes to, uh, the Nvidia aerial omniverse digital twin applications, we're already seeing, I, I would say partnership support Key psych, for example, is using the technology for its testing and simulation systems while we're seeing partners such as Deep Sig, Northeastern University and Samsung collaborating on six G research using Nvidia aerial AI radio frameworks. So this is, uh, showing that that vital ecosystem support is becoming, you know, more real. Also, I am seeing that the cloud stack software providers such as Arna Networks, canonical Red Hat and Wind River, and as well as network stack, uh, providers such as arcus are providing, you know, that the support for network and server, uh, 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 round 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, I think it's also important rounding out here to talk about the energy efficiency and sustainability aspects. Now the hope is, 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, uh, CPU technology, whether it's X 86, uh, based or, you know, using arm based implementations. The bottom line is the energy efficiency has to be there in order for the mobile deck work operators to, you know, offer a more compelling service, but also for them to meet their own in-house sustainability goals. And I don't think that's all at the table at all.

It's definitely something that the, uh, mobile network operators are keeping a CLO close eye on as they're looking at ways to innovate their, uh, overall mobile network implementations. And with that in mind, I thought was interesting that Orange Group is confident that O ran compliant radio units can achieve energy efficiencies comparable to two traditional ous. And so this is important.

This has been, uh, a bit of a debating point. You know, can open ran actually the least match or exceed, you know, the energy efficiencies that we're seeing with ongoing ru uh, implementations. And this could be, you know, a real, uh, you know, game, uh, a decision breaker that is if open ran cannot improve on traditional RS in this regard, then it could als it quite simply continue spinning its wheels in terms of, you know, market presence.

So what we're seeing is that when it comes to cloud ran ecosystem, which you basically is I would say a subset of the overall open ran, uh, realm, it's important that it can support virtualized base ban 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 gain gains. Now, so why is Orange confident about this? Well, it's really taking advantage of these new chip sets that are coming down and that cloud ran specifically can match from 2002 25 onwards.

That is the energy efficiency performance of those traditional rans and high capacity urban scenario. So this is not gonna be an overnight sensation, but a again, when it comes to those dense urban settings, we can see open ran, uh, again exceeding what traditional RAN could do in this particular area. And what else is, uh, you know, contributing to this while using massive MIMO technology, running again on those, uh, generic hardware, uh, platforms combined again with those purpose-built accelerators.

Now I believe there's been progress not only with the chip sets and accelerators, but I think Orange brings out a very important point. It's also with the dimensioning part, and this is again, where AI is helping play a role and with the newer chip sets that are coming out or have come out, it should, uh, as a result be able to provide highest capacity scenarios with a mix of FDD bands and TT DD bands in massive m Im up in a single server. So that's bringing a lot of, you know, 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, you know, well-established bands on the FDD and TDD side, uh, using massive MIO 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 chip set developments from various suppliers and also noting ran advances, uh, made by again, uh, Nvidia, uh, that orange is expecting performance crossover, uh, 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 just saying we're putting our money where our mouth is are just saying, okay, we believe that the Nvidia uh, proposition is going to help drive this. And that's tied back again to why the T-Mobile announcement on the AI ran side itself is so momentous.

And also, you know, spotlighting that Nvidia, Ericsson and Nokia are all on board. And this is just exciting. This is just gonna be, I think, great news we're making, you know, the RAN market segment itself more interesting.

That is, you know, more open ran, uh, 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 on the Future Group, uh, 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, you know, providing an episode next week as well. And with that, thank you everyone.

Have a great 5G and AI ran day.