AI-RAN is moving from lab to field, showing that a software-defined approach is the only viable way to build future AI-native wireless networks.<\/p>\n
Ahead of Mobile World Congress (MWC), running March 2-5 in Barcelona, NVIDIA and Nokia announced new AI-RAN collaborations with top telecom operators across Europe, Asia and North America, powered by NVIDIA AI-RAN platforms. Industry pioneers T-Mobile U.S., SoftBank and Indosat Ooredoo Hutchison (IOH) passed implementation milestones, taking NVIDIA-powered AI-RAN outdoors and over the air.<\/p>\n
New benchmarking results from partners like SynaXG<\/a> showed that AI-RAN running on NVIDIA platforms delivers high-speed, carrier-grade performance \u2014 meaning extreme reliability \u2014 across multiple 5G spectrum bands. And over 20 AI-RAN Alliance<\/a> demos built on NVIDIA platforms will be showcased at MWC, highlighting how AI is boosting 5G performance and efficiency, and unlocking new edge AI applications.<\/p>\n All of this represents momentum and convergence toward a common, software-defined foundation that will set the stage for secure, open and AI-native 6G systems<\/a>.<\/p>\n AI-RAN Goes From Lab to Live<\/p>\n Top telecom operators and partners are using NVIDIA platforms to bring AI-RAN to commercial deployment.\u00a0<\/p>\n T-Mobile U.S. demonstrated concurrent AI and RAN processing on NVIDIA AI-RAN platform using Nokia\u2019s CUDA-accelerated RAN software. In T-Mobile\u2019s over-the-air field environment, Nokia\u2019s AirScale massive multiple-input and multiple-output (MIMO) radio in the 3.7GHz band supported commercial devices running applications like video streaming, generative AI and AI-powered video captioning, alongside 5G.\u00a0<\/p>\n SoftBank\u2019s AITRAS live field trial achieved an industry-first, 16-layer massive MIMO using fully software-defined 5G running on NVIDIA\u2019s AI-RAN platform, marking an important technical milestone toward AI-RAN commercialization.\u00a0<\/p>\n IOH has implemented software-defined 5G with Nokia\u2019s vRAN software on NVIDIA AI-RAN platforms, moving from proof of concept to pre-commercial field validation. This milestone was showcased at MWC through Southeast Asia\u2019s first AI-powered 5G call, where AI and network intelligence operated seamlessly to enable secure, real-time cross-border connectivity, including responsive remote control of a robotic dog over the live 5G network. This achievement demonstrates IOH\u2019s readiness to scale AI-native network capabilities and bring intelligent connectivity to communities across Indonesia.<\/p>\n SynaXG demonstrated fully software-defined AI-RAN using NVIDIA AI Aerial<\/a> \u2014 a suite of accelerated computing platforms, software libraries and tools to build, train, simulate and deploy AI-native wireless networks \u2014 running 4G, 5G in both sub-6GHz [FR1] and millimeter wave [FR2] spectrum bands, alongside agentic AI workloads, on a single NVIDIA GH200 server. This marks the world\u2019s first implementation of AI-RAN on FR2 bands.<\/p>\n SynaXG\u2019s setup activated 20 component carriers with both a centralized unit (CU) and distributed unit (DU) on one platform, achieving a throughput of 36 Gbps<\/a> and under 10 milliseconds latency. These breakthrough results highlight AI-RAN-based 5G performance as well as seamless orchestration between AI and RAN workloads.<\/p>\n Tripled Pace of AI-RAN Innovation<\/p>\n This year\u2019s MWC will see triple the number of AI-RAN innovations over last year, with 26 out of 33 AI-RAN Alliance demos built using NVIDIA AI Aerial and a software-defined architecture.<\/p>\n Some of these demos include:<\/p>\n DeepSig<\/a> is reinventing how devices \u201cspeak\u201d to networks by letting AI learn a smarter signal format at both ends of the link \u2014 the communications channel that connects two devices. An AI\u2011native air interface jointly learns how to best encode and decode signals using neural techniques at the device and base station, removing pilot overheads and adapting to site\u2011specific channels. Early results on NVIDIA platforms show up to about 2x higher throughput and better spectral and energy efficiency from the same spectrum. \u201cAI-RAN is emerging as a unifying architecture for future radio networks,\u201d said Alex Choi, chair of the AI-RAN Alliance. \u201cBy aligning operators, vendors and researchers around software-defined, GPU-accelerated architectures, we are boosting innovation, validating new concepts quickly and building the foundation for AI-native 6G, now.\u201d<\/p>\n As intelligence moves into the physical world, autonomous systems such as robots and cars depend on AI-RAN networks to see, sense, reason and act.<\/p>\n Capgemini<\/a> is working within Project ULTIMO, a Horizon Europe-funded initiative, to show how AI-RAN can support large-scale autonomous mobility services across European cities. Autonomous shuttles equipped with the NVIDIA Jetson Orin<\/a> module process sensor data locally, while select video and telemetry streams are sent over 5G to agentic AI applications on NVIDIA AI-RAN servers. These workloads handle scene understanding, incident and safety detection, and accessibility insights at scale, while mission-critical 5G gets priority access to GPU resources.<\/p>\n A Growing Ecosystem<\/p>\n A growing ecosystem of partners is forming around NVIDIA-powered AI-RAN platforms, enabling operators to choose from a range of deployment solutions. NVIDIA Aerial RAN Computer (ARC) platforms harness the NVIDIA Grace CPU and a variety of GPUs, providing a high-performance, energy-efficient compute foundation for AI-native RAN infrastructure.<\/p>\n Quanta Cloud Technology (QCT)<\/a> is announcing commercial off-the-shelf AI-RAN products that support NVIDIA ARC platforms and Nokia software, giving operators standardized building blocks for AI-RAN. Laying the Foundation for Open, Secure, AI-Native 6G<\/p>\n NVIDIA\u2019s latest State of AI in Telecom<\/a> report showed that the industry is stepping up AI-native RAN and 6G investments \u2014 signaling a major intercept ahead of the traditional 6G deployment cycle, with 77% of respondents anticipating a much faster time to deployment of this new AI-native wireless network architecture.<\/p>\n This latest progress on software-defined AI-RAN is setting the stage for secure, open and AI-native 6G systems.<\/p>\n NVIDIA has already open sourced NVIDIA Aerial CUDA-accelerated RAN<\/a> libraries, fueling the pace of AI-RAN innovation. NVIDIA has also now joined the OCUDU<\/a> (Open CU DU) Ecosystem Foundation, hosted by the Linux Foundation, contributing to open source RAN software development to accelerate research and commercialization for next-generation wireless networks.<\/p>\n Learn more by meeting NVIDIA and partners at Mobile World Congress<\/a>. Explore key insights from the State of AI in Telecom<\/a> survey.<\/p>\n","protected":false},"excerpt":{"rendered":"AI-RAN is moving from lab to field, showing that a software-defined approach is the only viable way to…\n","protected":false},"author":2,"featured_media":498251,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[182,181,507,2250,10370,74,11719],"class_list":{"0":"post-498250","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-events","12":"tag-open-source","13":"tag-technology","14":"tag-telecommunications"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/498250","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=498250"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/498250\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/498251"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=498250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=498250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=498250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nSUTD, NVIDIA and partners will show how robots and autonomous vehicles can distribute their \u201cthinking\u201d across the device, edge and cloud \u2014 bringing split-inferencing from concept to implementation. By deciding in real time where each AI task runs, the demos prove how AI-RAN can meet tight latency, privacy and coverage service-level agreements to scale physical AI and vision language models through the network edge.
\nzTouch Networks and partners built an AI-RAN orchestration blueprint showing how operators can safely share GPUs across AI and RAN workloads. By using NVIDIA Multi-Instance GPU<\/a> technology, the blueprint steers resources in real time, maximizing GPU utilization and improving energy management while ensuring RAN quality of service. This is a key step for making multi-tenant AI-RAN solutions ready for commercial use, so operators can turn GPU capacity into revenue.
\nNortheastern University and SoftBank will demonstrate an AI switching solution for NVIDIA AI Aerial that flips in microseconds between AI and classic algorithms for channel estimation. This selects, in real time, the best possible processing solution at all times depending on conditions, improving stability and throughput while proving AI can coexist with classical approaches.<\/p>\n
\nSupermicro is extending support across the full NVIDIA AI-RAN portfolio, including NVIDIA ARC-Pro and NVIDIA RTX 6000-based configurations, as well as ARC-Compact systems with Nokia software.
\nWNC<\/a> has introduced a new AI-optimized indoor and outdoor open radio unit, integrated with NVIDIA AI Aerial Testbed and NVIDIA ARC platforms, that supports 5GA and 6G use cases.
\nEridan<\/a> has launched a 4T4R O-RU along with its 2T2R O-RU, which was integrated with NVIDIA AI Aerial, and a DU running on the NVIDIA DGX Spark desktop supercomputer, combining spectrally efficient radios with GPU-based baseband processing to create a powerful and portable outdoor base station.
\nLITEON<\/a> has completed integration of its sub-6 GHz and millimeter wave radio units with NVIDIA AI Aerial, and has expanded its collaboration with ecosystem partners like Supermicro and SynaXG to accelerate AI-RAN commercialization.<\/p>\n