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Virtualized 5G Tesbed using OpenAirInterface: Tutorial and Benchmarking Tests

M. Dória, V. Sousa, A. Campos, N. Oliveira, P. Eduardo, P. Filho, C. Lima, J. Guilherme, D. Luna, I. Rego, M. Fernandes, A. Neto

arXiv:2609.12972v1cs.NI

TL;DR

Because many works emphasize theory or performance results while step-by-step setup guidance is limited, this paper presents a tutorial for configuring and evaluating an OAI virtualized 5G network. It reports stable OAI-based 5G prototyping and potential for evaluating enhancements on a real low-cost platform.

  • Problem

    Many works emphasize theory or performance results, while step-by-step guidance for setup and experiments is comparatively limited.

    Source: §1 · p. 1

  • Method

    The paper provides setup and parameter-configuration instructions for an OAI virtualized 5G network and evaluates three use cases across spectrum, throughput, and ping.

    Source: §6 · p. 12

  • Results

    The study reports stable OAI code and potential for prototyping 5G enhancements, including evaluation on a real low-cost platform.

    Source: §6 · p. 12

  • Takeaways & Limitations

    The authors suggest that organizations can explore OAI for training and conceptual initiatives.

    Source: §6 · p. 12

    The evaluation does not yet cover multicell conditions, cochannel interference, or user metrics such as latency and error rate.

    Source: §6 · p. 12

Abstract

from arXiv · show

The development of 5G and its evolutionary path to 6G brings virtualization as close as possible to the antennas. Native 3GPP systems are now software running at servers boosted by accelerator cards to cope with computationally intense signal processing. Meanwhile, the Radio Frequency (RF) front-end is still proprietary hardware, sheltering specific PHY-layer procedures like passband amplification/modulation. This approach takes advantage of the software's flexibility while keeping the complex microsecond signal processing performance from modern telecommunication systems. This paper provides tutorial material on the Core Network and Radio Access Network of OpenAirInterface (OAI) 5G stack on top of Universal Software Radio Peripheral (USRP) platforms. A set of blueprints showcases OAI's ability to provide a virtualized 5G network with different transmission capabilities and the possibility to use it with commercial mobile phones. Configuration discussions and throughput benchmark analyses follow installation and deployment instructions. Our results show that 5G prototyping using OAI and USRP frontends can lead to good reproducibility and consistent throughput.

1 Introduction

The paper presents an OAI-and-USRP 5G tutorial focused on practical deployment and reproducibility, with network blueprints, configuration guidance, and throughput benchmarking.

1 Introduction

  • Virtualized 5G deployment needs flexible, cost-effective testing, while network stability under varied scenarios and loads matters for reliable service and economic survival.The introduction notes that downtime can frustrate users and contribute to churn.Source: §1 · p. 1
  • The paper provides practical OAI/USRP deployment guidance, blueprints spanning transmission capabilities and commercial-phone use, reproducibility support, throughput benchmarking, RAN configuration discussion, and open-source code.The tutorial also aims to address the lack of step-by-step setup and experimental guidance, including solutions to common issues.Source: §1 · pp. 1–2

1.1 Related Works

  • OAI offers open-source 3GPP implementation on general-purpose hardware and SDRs; 2020 studies covered 5G implementation, orchestration, RAN slicing, LTE V2X emulation, and C-RAN simulation.The OAI platform supports low-cost LTE or 5G NR deployments, and its public license lets contributors implement patented technology while retaining intellectual property rights.Source: §1.1 · p. 2
  • Studies from 2021–22 examined OAI/USRP testing, performance parameters, testbeds, FPGA acceleration, resource scaling, positioning, scheduling, and video use.The FPGA LDPC accelerator achieved more than 1.6 Gbps decoding throughput and up to 13x faster execution than single-core software implementations.Source: §1.1 · pp. 2–3
  • 2023 work covered scheduling, radio coverage, data rates, latency, and video streaming [D. and Chaudhari, 2023], but the cited literature lacked tutorial material for reproducibility.This paper addresses that gap with configuration discussions and throughput benchmarking using OAI and USRP.Source: §1.1 · p. 3

2 OpenAirInterface (OAI)

OAI is an open-source, 3GPP-aligned software stack for end-to-end 4G LTE and 5G NR, and its SDR support enables real-signal experiments with commercial devices. Its RAN, core, and OAM projects cover radio architecture, core functions, and network management.

2 OpenAirInterface (OAI)

  • OAI is open-source software for end-to-end 4G LTE and 5G NR systems, and SDR support allows real-signal experiments with commercial devices.The OpenAirInterface Software Alliance, founded in 2014 by EURECOM, operates the project; OAI organizes work into RAN, core-network, and OAM projects.Source: §2 · p. 3

2.1 OAI 5G RAN

  • OAI’s 3GPP-compliant RAN supports SA and NSA, with SA available in split or monolithic mode; this paper used monolithic SA for stability in its OAI version.In split mode, the gNB-CU handles RRC and PDCP, the gNB-DU handles PHY, MAC, and RLC, and the RU handles the radio part; monolithic mode combines the RAN components in one application.Source: §2.1 · p. 3

2.2 OAI Operations and Maintenance (OAM)

  • OAI OAM focuses on orchestration, monitoring, and maintenance of RAN and core functions and maintains O-RAN interfaces.Its solutions include FlexRIC, an O-RAN-compliant RIC, an E2 interface, and a Multi-access Edge Computing Platform (MEP).Source: §2.2 · p. 3

2.3 OAI 5G Core Network

  • OAI’s 3GPP-compliant 5G core supports SA and NSA, with Minimalist, Basic, and Slicing deployments adding network functions progressively.The core offers SPGW-U-tiny, VPP-UPF, and a Production grade UPF still under development, and can be deployed on bare metal or VMs, with Docker-Compose, or using Helm Chart.Source: §2.3 · p. 4

3 Installation/Deployment Tutorial

The tutorial presents a containerized workflow for installing and deploying the OAI 5G Core and gNB on bare-metal Ubuntu hosts. It specifies host prerequisites, deployment scripts and configuration options, and a way to check connectivity through AMF logs.

3 Installation/Deployment Tutorial

  • The containerized deployment requires at least 4 CPU cores, 16 GB RAM, 1.5 GB free storage, Ubuntu 20.04 LTS or newer, Python 3, Docker, and Docker Compose.The containers run in privileged mode, and two shell scripts automate deployment of the 5GC and gNB.Source: §3 · p. 4
  • The 5GC script installs dependencies and certificates, configures packet forwarding and Docker, and starts the basic 5GC before services.sh installs and deploys the gNB.The 5GC script also handles Docker images and synchronization of 5GC components; services.sh accepts configuration parameters.Source: §3 · p. 4
  • After connecting a USRP and verifying its IP address, operators use services.sh options to select N310 or B210 configurations with specified PRB counts, or stop the gNB containers.Available options are n106, n162, and n273 for N310; b106 and b162 for B210; and stop to finalize the gNB containers.Source: §3 · p. 5
  • The oai-amf container logs, accessed with docker logs oai-amf -f, indicate the connection status of the 5GC, gNB, and connected UEs.Source: §3 · p. 5

4 Test Scenarios

The test scenarios vary carrier bandwidth from a 3.7 GHz starting point using a USRP N310 with the 7.2x split and a Motorola G50 UE. The section describes the infrastructure, gNB configurations, and SIM setup used for these tests.

4 Test Scenarios

  • The over-the-air tests vary carrier bandwidth from 3.7 GHz, using a USRP N310 for the RF front-end and Low-PHY layer with the 7.2x split and a Motorola G50 UE.Table 1 summarizes the bandwidth test scenarios, but the supplied passage does not provide their individual bandwidth values.Source: §4 · p. 5, Table 1 · p. 5

4.1 Infrastructure Description

  • The setup uses a 20-core Lenovo ThinkSystem SR630 server, a USRP N310 connected over 10 Gbps DAC, and two Ettus LP0965 antennas; the Motorola G50 runs Android 11/12 on battery.Tests kept the phone battery above 50%, without an external power source, at an ambient temperature of 21–25ºC.Source: §4.1 · p. 5

4.2 gNB Parameters configuration

  • For SISO, the gNB configuration sets min_rxtxtime to 5 ms, disables 256-QAM and MIMO-related CSIRS/SRS, and uses one antenna port; nb_tx and nb_rx are also set to 1.The configuration describes transmitter and receiver attenuation values from 0 to 10, with 10 representing maximum attenuation; max_rxgain is recommended as 75 for the N310.Source: §4.2 · p. 5
  • The gNB configuration defines slot timing and frequency in NR-ARFCN: it selects band 78, sets Point A to 3.7 GHz and the SSB center to 3.72 GHz, and matches uplink bandwidth settings to downlink.The 106-PRB configuration corresponds to 40 MHz; the text also identifies configurations for 162 PRBs/60 MHz and 273 PRBs/100 MHz.Source: §4.2 · pp. 6–7

4.3 UE configuration

  • The UE setup guide covers installing and configuring Sysmocom SIM cards and requires compatible IMSI, OPc, and Ki values for authentication with the configured 5G network.SIM cards from other manufacturers can also be used if those parameters are configured compatibly.Source: §4.3 · p. 7

5 Results

The results cover spectrum occupation, laboratory RSRP coverage, and throughput and RTT across bandwidth settings, UE-to-UE communication, and gNB–UE distances.

5.1 Use Case 1: Spectrum Occupation

  • The 40, 60, and 100 MHz configurations fully occupied their respective bands during transmission, using 106, 162, and 273 PRBs, respectively.Measurements used a spectrum analyzer centered at 3.75 GHz, with a 100 MHz trace spanning 3.7–3.8 GHz.Source: Figure 5 · p. 8, §5.1 · pp. 8–9

5.2 Use Case 2: Coverage Evaluation

  • The coverage map measured RSRP from -102.0 dBm to -73.2 dBm, with strongest signals near the transmission setup and weakest levels in the lower-left lab region.Central regions measured -84.0 to -76.8 dBm; the weakest lower-left areas measured -94.8 to -102.0 dBm and may experience connectivity issues or lower data rates.Source: Figure 7 · p. 9, §5.2 · p. 9

5.3.1 Channel-Ideal Scenario

  • Mean throughput rose from 135.69 Mbps at 106 PRBs to 207.66 Mbps at 162 PRBs and 238.60 Mbps at 273 PRBs, while variability was highest at 273 PRBs.The corresponding standard deviations were 1.78, 1.98, and 29.02 Mbps; the 100 MHz configuration operated near the USRP sampling-rate capacity. Each PRB setting was tested in 10 transmissions of 180 seconds.Source: §5 · p. 8, §5.3.1 · pp. 9–10, Table 3 · p. 10
  • RTT maximum and mean values increased with PRBs, and RTT standard deviation rose from 3.71 ms at 106 PRBs to 10.42 ms at 273 PRBs; packet loss was zero across experiments.The results associate higher bandwidth allocations with greater latency variability.Source: Figure 12 · p. 10, §5.3.1 · pp. 10–11

5.3.2 Two UEs Evaluation Scenario

  • At 106 PRBs, maximum throughput was 16.45 Mbps for UE-to-UE versus 245 Mbps for gNB-to-UE, and mean throughput was 14.75 versus 135.69 Mbps, respectively.The paper attributes the maximum-throughput gap to uplink limitations and notes that UE-to-UE mean throughput depends on the UL/DL TDD slot ratio.Source: Table 5 · p. 11, §5.3.2 · p. 11, Figure 13 · p. 11
  • In the UE-to-UE scenario, maximum and mean RTTs were more than twice those in the gNB-to-UE scenario, and RTT was more variable.The paper attributes the greater variability and latency to bidirectional uplink/downlink transmission and additional gNB processing to forward data between UEs.Source: Figure 14 · p. 11, §5.3.2 · p. 11

5.3.3 Distance Evaluation Scenario

  • At 12 m, mean throughput was 102.35 Mbps, while maximum throughput ranged from 119 to 153 Mbps across distances and throughput variability increased with distance.The results indicate declining mean throughput and greater variability at longer distances, despite high maximum bandwidth capability.Source: Table 7 · p. 11, §5.3.3 · p. 11, Figure 15 · p. 12

6 Conclusions and Future Works

The paper presents instructions and parameter configurations for a virtualized OAI 5G network, with three use cases evaluating network- and user-side performance. Its findings demonstrate OAI’s stability and prototyping potential on a real low-cost platform, while identifying multicell measurements and additional user metrics as future work.

6 Conclusions and Future Works

  • The paper presents instructions and parameter configurations for a virtualized OAI 5G network and proposes three use cases covering spectrum-related, throughput, and ping evaluations.The use cases consider both network and user perspectives.Source: §6 · p. 12
  • The findings demonstrate OAI code’s stability and potential for prototyping 5G enhancements and evaluating them on a real low-cost platform.The authors note that this platform could support exploration by industry-leading vendors, small and medium companies, start-ups, and academic institutions, from training to conceptual initiatives.Source: §6 · p. 12
  • Future work should measure a multicell environment, including cochannel interference and user-related metrics such as latency and error rate.Source: §6 · p. 12

Funding

The paper reports its funding, author contributions, competing-interests statement, and location of study data and tutorial materials.

Funding

  • The research was partially funded by Lenovo under its Brazilian Informatics Law R&D investment and by CAPES Finance Code 001.Source: Funding · p. 12

Authors’ Contributions

  • Authors contributed to study conception, validation, methodology, experiments, writing, and supervision, and all approved the final manuscript.Source: Authors’ Contributions · p. 12

Competing interests

Availability of data and materials

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