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X5G: An Open, Programmable, Multi-vendor, End-to-end, Private 5G O-RAN Testbed with NVIDIA ARC and OpenAirInterface

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arxiv 2406.15935 v5 pith:WS737LGX submitted 2024-06-22 cs.NI

classification cs.NI
keywords programmablesoftwareintegrationintelligentnetworkperformanceaerialcell
verification ladder T0 review T1 audit T2 compute T3 formal

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As Fifth generation (5G) cellular systems transition to softwarized, programmable, and intelligent networks, it becomes fundamental to enable public and private 5G deployments that are (i) primarily based on software components while (ii) maintaining or exceeding the performance of traditional monolithic systems and (iii) enabling programmability through bespoke configurations and optimized deployments. This requires hardware acceleration to scale the Physical (PHY) layer performance, programmable elements in the Radio Access Network (RAN) and intelligent controllers at the edge, careful planning of the Radio Frequency (RF) environment, as well as end-to-end integration and testing. In this paper, we describe how we developed the programmable X5G testbed, addressing these challenges through the deployment of the first 8-node network based on the integration of NVIDIA Aerial RAN CoLab Over-the-Air (ARC-OTA), OpenAirInterface (OAI), and a near-real-time RAN Intelligent Controller (RIC). The Aerial Software Development Kit (SDK) provides the PHY layer, accelerated on Graphics Processing Unit (GPU), with the higher layers from the OAI open-source project interfaced with the PHY through the Small Cell Forum (SCF) Functional Application Platform Interface (FAPI). An E2 agent provides connectivity to the O-RAN Software Community (OSC) near-real-time RIC. We discuss software integration, network infrastructure, and a digital twin framework for RF planning. We then profile the performance with up to 4 Commercial Off-the-Shelf (COTS) smartphones for each base station with iPerf and video streaming applications, as well as up to 25 emulated User Equipments (UEs), measuring a cell rate higher than 1.65 Gbps in downlink and 143 Mbps in uplink.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Driving Innovation in 6G Wireless Technologies: The OpenAirInterface Approach

    cs.NI 2024-12 unverdicted novelty 3.0 of 10

    The paper describes the OpenAirInterface open-source 5G/6G platform, its performance on selected testbeds, and argues that such open-source systems will drive 6G research.

  2. Securing Open RAN: A Survey of Cryptographic Challenges and Emerging Solutions for 5G

    cs.CR 2025-06 conditional novelty 2.0 of 10

    A survey of cryptographic challenges in Open RAN for 5G, covering bidding-down attacks, interface encryption gaps, and 256-bit ciphers like SNOW-V, ZUC-256, and AES-256.

  3. Advancements in Mobile Edge Computing and Open RAN: Leveraging Artificial Intelligence and Machine Learning for Wireless Systems

    cs.NI 2025-02 unverdicted

    A reading report on MEC and Open RAN concludes that AI and deep reinforcement learning improve offloading and network control, but it provides no new measurements.

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