1. [Topics](/topics) 2. Telecommunications ### # Developer Resources for Telecommunications A hub of news, SDKs, technical resources, and more for developers working in telecommunications. #### Find tutorials, samples, videos, and more: [Explore Resources](#library) #### Use Cases: - Accelerated 5G and 6G RAN - Autonomous Networks - Customer Service ## Get Started With Telecommunications Use Cases ### Deploy AI-Native 5G and 6G Networks With Accelerated RAN Developers can use NVIDIA AI Aerial™ libraries to build a software-defined, CUDA®-accelerated radio access network (RAN) that runs AI and wireless workloads on the same accelerated infrastructure. Digital twin simulation tools enable realistic radio-frequency (RF) testing and validation before live deployment, speeding up iteration and reducing risk. - Visit: [NVIDIA AI Aerial Page](/industries/telecommunications/ai-aerial) - Explore: [NVIDIA AI Aerial Docs](https://docs.nvidia.com/aerial) - Go to GitHub: [NVIDIA AI Aerial](https://github.com/NVIDIA/aerial-cuda-accelerated-ran) ### Automate Network Operations With Agentic AI and Digital Twins Using NVIDIA NeMo™, NIM™ microservices, and AI Blueprints, developers can build AI agents that analyze network data, detect anomalies, and recommend or execute configuration changes. These workflows help automate optimization and troubleshooting in complex, real-time telecom environments. - Read Blog: [New NVIDIA AI Blueprint Helps Automate Telco Network Configuration](https://blogs.nvidia.com/blog/ai-blueprint-telco-network-configuration/?utm_source=chatgpt.com) - Start Building: [Intent‑Driven 5G Energy Efficiency NVIDIA Blueprint](https://build.nvidia.com/viavi/intent-driven-ran-energy-efficiency) ### Build Customer Service Agents With Generative AI Developers can create voice and chat agents with NVIDIA NeMo and Riva that understand, summarize, and respond to customer issues across channels. GPU-accelerated inference enables real-time, scalable deployment for contact centers and digital support experiences. - Learn More: [Deploy Generative AI in Telecom With NVIDIA NIM](https://www.nvidia.com/en-us/ai/nim-for-telco/?utm) - Start Building: [Build an AI Virtual Assistant Blueprint](https://build.nvidia.com/nvidia/ai-virtual-assistant-for-customer-service?ncid=pa-srch-goog-138224-vt53-1) - Go to GitHub: [NVIDIA Voice Agent Examples](https://github.com/NVIDIA/voice-agent-examples) ## Explore Tools and Technologies for Telecommunications **NVIDIA Aerial CUDA-Accelerated RAN** ### 5G and 6G RAN NVIDIA Aerial CUDA-Accelerated RAN (ACAR) is an SDK for building commercial-grade, AI-native, 3rd Generation Partnership Project (3GPP)- and O-RAN-compliant 5G and 6G Next-Generation Node B (gNB) software on NVIDIA-accelerated computing platforms. [Get Started With ACAR](https://github.com/NVIDIA/aerial-cuda-accelerated-ran) **NVIDIA Aerial Framework** ### Real-Time 5G and 6G Applications NVIDIA Aerial Framework is a framework for generating high-performance, CUDA-accelerated 5G and 6G pipelines from high-level programming languages. [Get Started With Aerial Framework](https://github.com/NVIDIA/aerial-framework) **NVIDIA Aerial Omniverse Digital Twin** ### Network Digital Twin NVIDIA Aerial Omniverse™ Digital Twin (AODT) is a large-scale simulation platform that leverages NVIDIA GPUs to enable highly realistic twinning of radio environments and network behavior. [Get Started With AODT](https://docs.nvidia.com/aerial/aerial-dt/index.html) **NVIDIA Sionna** ### 6G Research NVIDIA® Sionna™ is a GPU-accelerated open source library for research in communication systems. It's differentiable and features a lightning-fast ray tracer for radio propagation, a versatile link-level simulator, and system-level simulation capabilities. [Get Started With Sionna](/sionna) **NVIDIA NIM** ### Agentic AI NVIDIA NIM is a set of easy-to-use microservices designed to accelerate the deployment of generative AI models across any cloud or data center. [Get Started With NIM](/nim) **NVIDIA Nemotron** ### Agentic AI NVIDIA Nemotron™ is a family of efficient, mostly open multimodal models that include open datasets and recipes for building agentic AI. [Get Started With Nemotron](/nemotron) **NVIDIA NeMo** ### Agentic AI NVIDIA NeMo is an end-to-end platform for developing custom generative AI anywhere. Deliver enterprise-ready models with precise data curation, cutting-edge customization, retrieval-augmented generation (RAG), and accelerated performance. [Get Started With NeMo](https://www.nvidia.com/en-us/ai-data-science/products/nemo/) **NVIDIA Riva** ### Conversational AI NVIDIA Riva is an SDK for building and deploying AI applications that fuse vision, speech, and other sensors. It offers a complete workflow to build, train, and deploy GPU-accelerated AI systems that can use visual cues such as gestures and gaze along with speech in context. [Get Started With Riva](/riva?ncid=pa-srch-goog-138224-vt53-1) **NVIDIA DOCA** ### Data Center Workloads By harnessing the power of NVIDIA BlueField® DPUs and SuperNICs, NVIDIA DOCA™ enables the rapid creation of applications and services that offload, accelerate, and isolate data center workloads. [Get Started With DOCA](/networking/doca) ## Telecommunications Learning Library The rows below are the raw result records for this component — one row per record. Column names are the source index fields; the full data is also downloadable in the links that follow. | title | featured | x_formats | document_url | technologies | document_date | short_summary | document_title | learning_level | x_content_types | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Improve AI-Native 6G Design with the NVIDIA Aerial Omniverse Digital Twin | false | blog | https://developer.nvidia.com/blog/improve-ai-native-6g-design-with-the-nvidia-aerial-omniverse-digital-twin/ | Aerial Omniverse Digital Twin | 2025-12-09T05:00:00.000Z | Explore how AODT improves AI-native 6G network design with high-fidelity radio simulation. | Improve AI-Native 6G Design with the NVIDIA Aerial Omniverse Digital Twin | Technical - Intermediate | Explainer | | Introducing NVIDIA Aerial Research Cloud for Innovations in 5G and 6G | false | blog | https://developer.nvidia.com/blog/introducing-aerial-research-cloud-for-innovations-in-5g-and-6g/ | AI Aerial | 2023-03-23T04:00:00.000Z | Get introduced to Aerial Research Cloud, NVIDIA's programmable 5G/6G research sandbox. | Introducing NVIDIA Aerial Research Cloud for Innovations in 5G and 6G | Technical - Beginner | Overview | | Deploy AI-RAN at Cell Sites with NVIDIA ARC-Compact | false | blog | https://developer.nvidia.com/blog/deploy-ai-ran-at-cell-sites-with-nvidia-arc-compact/ | AI Aerial | 2025-05-18T04:00:00.000Z | Deploy AI-RAN at distributed cell sites using the NVIDIA ARC-Compact reference architecture. | Deploy AI-RAN at Cell Sites with NVIDIA ARC-Compact | Technical - Intermediate | How-to | | Hello Sionna! A Demo of the First Open Source Library for Physical Layer Research | false | video | https://www.youtube.com/watch?v=cYUNE4i4Q4E | Sionna | 2022-03-22T04:00:00.000Z | Watch a quickstart demo of the Sionna open-source library for physical-layer research. | Hello Sionna! A Demo of the First Open Source Library for Physical Layer Research | Technical - Beginner | Demo | | NVIDIA Aerial CUDA-Accelerated RAN | false | webpage | https://developer.nvidia.com/aerial-cuda-accelerated-ran | Aerial CUDA Accelerated RAN | 2024-04-22T04:00:00.000Z | Get introduced to Aerial CUDA-Accelerated RAN, NVIDIA's software-defined 5G/6G physical layer. | NVIDIA Aerial CUDA-Accelerated RAN | Technical - Beginner | Overview | | aerial-sample-apps (GitHub) | true | code | https://github.com/NVIDIA/aerial-sample-apps | Aerial CUDA Accelerated RAN | 2026-04-29T04:00:00.000Z | Study distributed apps (dApps) using the E3 interface for real-time RAN data processing on Aerial Testbed. | aerial-sample-apps (GitHub) | Technical - Intermediate | Samples | | Sionna — An Open-Source Library for 6G Research | false | webpage | https://developer.nvidia.com/sionna | Sionna | 2022-03-22T04:00:00.000Z | Get introduced to Sionna, NVIDIA's open-source library for physical-layer 6G research. | Sionna — An Open-Source Library for 6G Research | Technical - Beginner | Overview | | NVIDIA 6G Research Cloud Platform | false | video | https://www.youtube.com/watch?v=WBK5pmQDquw | AI Aerial | 2024-03-25T04:00:00.000Z | Watch an overview of the NVIDIA 6G Research Cloud platform for accelerated wireless research. | NVIDIA 6G Research Cloud Platform | Technical - Beginner | Overview | | aerial-framework (GitHub) | false | code | https://github.com/NVIDIA/aerial-framework | Aerial Framework | 2025-12-10T05:00:00.000Z | Fork the Aerial Framework toolchain for generating GPU-accelerated 5G/6G pipelines from Python. | aerial-framework (GitHub) | Technical - Beginner | Samples | | Sionna Documentation | false | webpage | https://nvlabs.github.io/sionna/ | Sionna | 2022-03-22T04:00:00.000Z | Reference the Sionna documentation for APIs, tutorials, and examples. | Sionna Documentation | Technical - Intermediate | Documentation | | NVIDIA Aerial Omniverse Digital Twin Boosts Development of AI-Native Wireless and Deployment Flexibility | false | blog | https://developer.nvidia.com/blog/nvidia-aerial-omniverse-digital-twin-boosts-development-of-ai-native-wireless-and-deployment-flexibility/ | Aerial Omniverse Digital Twin | 2025-03-19T04:00:00.000Z | Explore how the Aerial Omniverse Digital Twin accelerates AI-native wireless development and deployment. | NVIDIA Aerial Omniverse Digital Twin Boosts Development of AI-Native Wireless and Deployment Flexibility | Technical - Intermediate | Explainer | | AI-RAN Goes Live and Unlocks a New AI Opportunity for Telcos | false | blog | https://developer.nvidia.com/blog/ai-ran-goes-live-and-unlocks-a-new-ai-opportunity-for-telcos/ | AI Aerial | 2024-11-12T05:00:00.000Z | Explore how AI-RAN converges AI and RAN workloads on shared infrastructure to unlock new telco revenue. | AI-RAN Goes Live and Unlocks a New AI Opportunity for Telcos | Technical - Intermediate | Explainer | | Automating Telco Network Design using NVIDIA NIM and NVIDIA NeMo | false | blog | https://developer.nvidia.com/blog/automating-telco-network-design-using-nvidia-nim-and-nvidia-nemo/ | NeMo, NIM | 2024-07-23T04:00:00.000Z | Automate telco network design using NVIDIA NIM and NeMo to generate TOSCA templates. | Automating Telco Network Design using NVIDIA NIM and NVIDIA NeMo | Technical - Intermediate | Tutorial | | Design and Test 5G and 6G Networks Using NVIDIA Aerial Omniverse Digital Twin | false | video | https://www.youtube.com/watch?v=J5-rkgL2dFA | Aerial Omniverse Digital Twin | 2024-04-23T04:00:00.000Z | See how AODT designs and tests 5G/6G networks with high-fidelity ray-traced simulation. | Design and Test 5G and 6G Networks Using NVIDIA Aerial Omniverse Digital Twin | Technical - Beginner | Demo | | Building Sovereign AI Models — Technical Overview | false | pdf | https://nvdam.widen.net/s/zqhnctvvnb/sovereign-ai-technical-overview | NeMo Curator, NeMo Guardrails, Nemotron, NIM, TensorRT-LLM | 2024-10-10T04:00:00.000Z | Learn end-to-end sovereign LLM development covering data curation, training, safety, and deployment. | Building Sovereign AI Models — Technical Overview | Technical - Intermediate | Explainer | | Build With NVIDIA AI Grid Reference Design | false | webpage | https://docs.nvidia.com/ai-grid/whitepapers/ai-grid-reference-design/ | AI Grid Reference Architecture | 2026-03-17T04:00:00.000Z | Reference the AI Grid design whitepaper guiding service providers deploying distributed AI-native services. | Build With NVIDIA AI Grid Reference Design | Technical - Advanced | Documentation | | Sionna RT: Scene Creation with Blender using OpenStreetMap | false | video | https://www.youtube.com/watch?v=7xHLDxUaQ7c | Sionna | 2023-03-21T04:00:00.000Z | Build Sionna RT scenes in Blender from OpenStreetMap data for ray-traced wireless simulation. | Sionna RT: Scene Creation with Blender using OpenStreetMap | Technical - Intermediate | Tutorial | | NVIDIA AI Grid Documentation | false | webpage | https://docs.nvidia.com/ai-grid/index.html | AI Grid Reference Architecture | 2026-03-17T04:00:00.000Z | Reference the AI Grid docs covering geographically distributed AI infrastructure as a unified platform. | NVIDIA AI Grid Documentation | Technical - Intermediate | Documentation | | How NVIDIA AODT Powers Network Digital Twins | true | video | https://www.youtube.com/watch?v=BGV1vZ9lX4s | Aerial Omniverse Digital Twin | 2026-03-17T04:00:00.000Z | Watch how AODT powers wireless network digital twins for AI-native 6G research. | How NVIDIA AODT Powers Network Digital Twins | Technical - Beginner | Demo | | NVlabs/sionna-rk — Sionna Research Kit (GitHub) | false | code | https://github.com/NVlabs/sionna-rk | Sionna | 2026-03-19T04:00:00.000Z | Fork the Sionna Research Kit: a DGX Spark + OpenAirInterface platform for AI-native RAN experimentation. | NVlabs/sionna-rk — Sionna Research Kit (GitHub) | Technical - Intermediate | Samples | | Enhanced DU Performance and Workload Consolidation for 5G/6G with NVIDIA Aerial CUDA-Accelerated RAN | false | blog | https://developer.nvidia.com/blog/enhanced-du-performance-and-workload-consolidation-for-5g-6g-with-aerial-cuda-accelerated-ran/ | Aerial CUDA Accelerated RAN | 2024-04-22T04:00:00.000Z | Explore enhanced DU performance and workload consolidation for 5G/6G using Aerial CUDA-Accelerated RAN. | Enhanced DU Performance and Workload Consolidation for 5G/6G with NVIDIA Aerial CUDA-Accelerated RAN | Technical - Advanced | Explainer | | Advanced RAG Techniques for Telco O-RAN Specifications Using NVIDIA NIM Microservices | false | blog | https://developer.nvidia.com/blog/advanced-rag-techniques-for-telco-o-ran-specifications-using-nvidia-nim-microservices/ | NeMo Retriever, NIM | 2024-10-10T04:00:00.000Z | Build advanced RAG pipelines over O-RAN specifications using NVIDIA NIM microservices. | Advanced RAG Techniques for Telco O-RAN Specifications Using NVIDIA NIM Microservices | Technical - Advanced | Tutorial | | Building the AI Grid with NVIDIA: Orchestrating Intelligence Everywhere | false | blog | https://developer.nvidia.com/blog/building-the-ai-grid-with-nvidia-orchestrating-intelligence-everywhere/ | AI Grid Reference Architecture, NIM | 2026-03-17T04:00:00.000Z | Explore the NVIDIA AI Grid reference for orchestrating inference across distributed telco infrastructure. | Building the AI Grid with NVIDIA: Orchestrating Intelligence Everywhere | Technical - Intermediate | Explainer | | Building Telco Reasoning Models for Autonomous Networks with NVIDIA NeMo | false | blog | https://developer.nvidia.com/blog/building-telco-reasoning-models-for-autonomous-networks-with-nvidia-nemo/ | NeMo Framework | 2026-02-28T05:00:00.000Z | Build telco reasoning models for autonomous networks using the NVIDIA NeMo framework. | Building Telco Reasoning Models for Autonomous Networks with NVIDIA NeMo | Technical - Advanced | Tutorial | | Jumpstarting Link-Level Simulations with NVIDIA Sionna | false | blog | https://developer.nvidia.com/blog/jumpstarting-link-level-simulations-with-sionna/ | Sionna | 2022-03-22T04:00:00.000Z | Build GPU-accelerated link-level wireless simulations using the open-source NVIDIA Sionna library. | Jumpstarting Link-Level Simulations with NVIDIA Sionna | Technical - Intermediate | Tutorial | | Aerial Omniverse Digital Twin Documentation | false | webpage | https://docs.nvidia.com/aerial/aerial-dt/index.html | Aerial Omniverse Digital Twin | 2025-03-19T04:00:00.000Z | Reference the Aerial Omniverse Digital Twin documentation for installation, APIs, and scene authoring. | Aerial Omniverse Digital Twin Documentation | Technical - Intermediate | Documentation | | Accelerating the Path to 6G With an AI-Native Wireless Stack | false | video | https://www.youtube.com/watch?v=f40DlANmJmo | AI Aerial | 2025-10-28T04:00:00.000Z | See how the NVIDIA AI-native wireless stack accelerates the path to 6G. | Accelerating the Path to 6G With an AI-Native Wireless Stack | Technical - Beginner | Overview | | NVIDIA Aerial Framework Documentation | true | webpage | https://docs.nvidia.com/aerial/framework/latest/ | Aerial Framework | 2025-12-10T05:00:00.000Z | Reference the Aerial Framework docs for real-time signal-processing pipelines with microsecond latency. | NVIDIA Aerial Framework Documentation | Technical - Intermediate | Documentation | | aerial-cuda-accelerated-ran (GitHub) | false | code | https://github.com/NVIDIA/aerial-cuda-accelerated-ran | Aerial CUDA Accelerated RAN | 2026-04-22T04:00:00.000Z | Fork the open-source Aerial CUDA-Accelerated RAN 5G/6G physical-layer stack. | aerial-cuda-accelerated-ran (GitHub) | Technical - Beginner | Samples | | Transforming Telco Network Operations Centers with NVIDIA NeMo Retriever and NVIDIA NIM | false | blog | https://developer.nvidia.com/blog/transforming-telco-network-operations-centers-with-nvidia-nemo-retriever-and-nvidia-nim/ | NeMo Retriever, NIM | 2024-07-23T04:00:00.000Z | Build agentic NOC assistants that triage incidents using NeMo Retriever and NIM microservices. | Transforming Telco Network Operations Centers with NVIDIA NeMo Retriever and NVIDIA NIM | Technical - Intermediate | Tutorial | | Powering AI-Native 6G Research with the NVIDIA Sionna Research Kit | false | blog | https://developer.nvidia.com/blog/powering-ai-native-6g-research-with-the-nvidia-sionna-research-kit/ | Sionna | 2025-10-28T04:00:00.000Z | Explore the Sionna Research Kit for hardware-in-the-loop AI-native 6G research on DGX Spark. | Powering AI-Native 6G Research with the NVIDIA Sionna Research Kit | Technical - Intermediate | Explainer | | Aerial CUDA-Accelerated RAN Documentation | false | webpage | https://docs.nvidia.com/aerial/cuda-accelerated-ran/latest/index.html | Aerial CUDA Accelerated RAN | 2024-04-22T04:00:00.000Z | Reference the Aerial CUDA-Accelerated RAN documentation for installation, configuration, and APIs. | Aerial CUDA-Accelerated RAN Documentation | Technical - Intermediate | Documentation | | Aerial Framework Python Development Guide | false | webpage | https://docs.nvidia.com/aerial/framework/latest/developer_guide/python.html | Aerial Framework | 2025-12-10T05:00:00.000Z | Reference the Aerial Framework Python guide covering JAX PHY, MLIR-TensorRT lowering, and Sionna datasets. | Aerial Framework Python Development Guide | Technical - Intermediate | Documentation | | NVIDIA Open Sources Aerial Software to Accelerate AI-Native 6G | true | blog | https://blogs.nvidia.com/blog/open-source-aerial-ai-native-6g/ | AI Aerial | 2025-10-28T04:00:00.000Z | Discover how NVIDIA's open-sourced Aerial software accelerates AI-native 6G research and development. | NVIDIA Open Sources Aerial Software to Accelerate AI-Native 6G | Technical - Beginner | News | | AI Agent for Telecom Network Configuration Planning | false | hands-on | https://build.nvidia.com/nvidia/telco-network-configuration | NIM | 2024-10-10T04:00:00.000Z | Try an agentic AI blueprint that automates and optimizes RAN parameter configuration with LLMs. | AI Agent for Telecom Network Configuration Planning | Technical - Intermediate | Demo | | NVIDIA Aerial Omniverse Digital Twin | false | webpage | https://developer.nvidia.com/aerial-omniverse-digital-twin | Aerial Omniverse Digital Twin | 2025-03-19T04:00:00.000Z | Get introduced to the Aerial Omniverse Digital Twin for high-fidelity wireless simulation. | NVIDIA Aerial Omniverse Digital Twin | Technical - Beginner | Overview | | pyAerial Documentation | false | webpage | https://docs.nvidia.com/aerial/cuda-accelerated-ran/latest/pyaerial/index.html | Aerial CUDA Accelerated RAN | 2024-04-22T04:00:00.000Z | Reference pyAerial APIs for Python-based physical-layer simulation and prototyping. | pyAerial Documentation | Technical - Intermediate | Documentation | | Part 1: Getting Started with Sionna | true | hands-on | https://nvlabs.github.io/sionna/phy/tutorials/notebooks/Sionna_tutorial_part1.html | Sionna | 2022-03-22T04:00:00.000Z | Build a 5G NR point-to-point link in Sionna and train a neural receiver end-to-end. | Part 1: Getting Started with Sionna | Technical - Beginner | Tutorial | | NVlabs/sionna (GitHub) | false | code | https://github.com/NVlabs/sionna | Sionna | 2026-04-01T04:00:00.000Z | Fork Sionna 2.0: open-source ray tracer (RT), link-level simulator (PHY), and system-level simulator (SYS). | NVlabs/sionna (GitHub) | Technical - Beginner | Samples | | NVIDIA AI Aerial Documentation | false | webpage | https://docs.nvidia.com/aerial/index.html | AI Aerial | 2025-10-28T04:00:00.000Z | Reference NVIDIA AI Aerial documentation for the full software-defined 5G/6G stack. | NVIDIA AI Aerial Documentation | Technical - Intermediate | Documentation | | Maximize Spectral Efficiency with AI-Native RAN and NVIDIA AI Aerial | false | blog | https://developer.nvidia.com/blog/maximize-spectral-efficiency-with-ai-native-ran-and-nvidia-ai-aerial | AI Aerial | 2026-07-06T00:00:00.000Z | Learn about the benefits of GPU acceleration in the RAN, and how AI-native RAN helps close the massive MIMO performance gap. It shows how NVIDIA AI Aerial enables a new class of Layer 1 and Layer 2 algorithms designed to unlock greater spectral efficiency in real-world deployments. | Maximize Spectral Efficiency with AI-Native RAN and NVIDIA AI Aerial | Technical - Intermediate | Explainer | | Five Takeaways from NVIDIA 6G Developer Day 2024 | false | blog | https://developer.nvidia.com/blog/five-takeaways-from-nvidia-6g-developer-day-2024/ | AI Aerial | 2024-12-14T00:00:00.000Z | Survey key 6G research themes and NVIDIA tooling announcements from 6G Developer Day 2024. | Five Takeaways from NVIDIA 6G Developer Day 2024 | Technical - Beginner | Overview | | cuBB Developer Guide | false | webpage | https://docs.nvidia.com/aerial/cuda-accelerated-ran/latest/cubb/index.html | Aerial CUDA Accelerated RAN | 2024-04-21T00:00:00.000Z | Reference the cuBB guide covering cuPHY, cuMAC, and pyAerial for 5G gNB L1 development. | cuBB Developer Guide | Technical - Advanced | Documentation | [Download the raw results data (JSON)](https://developer.nvidia.com/search-data/telecommunications.json) ## More Resources ![Decorative image representing Developer Community](https://developer.download.nvidia.com/icons/m48-people-group.svg) ### Join the NVIDIA 6G Developer Program ![Decorative image representing Training and Certification](https://developer.download.nvidia.com/icons/m48-certification-ribbon-2.svg) ### Get Training and Certification ![Decorative image representing Inception for Startups](https://developer.download.nvidia.com/icons/m48-ai-startup.svg) ### Read NVIDIA Tech Blogs