# Development of open radio access networks (O-RAN) for real-time robotic teleoperation

## TL;DR

This paper presents a real-world testbed for open radio access networks (O-RAN) to enable low-latency robotic teleoperation with real-time performance validation.

## Contribution

A reproducible O-RAN testbed with haptic robotic control and low-power mobile dongles for real-time teleoperation is developed.

## Key findings

- The testbed achieves sub-one-second latency and 12% block error rate for haptic robotic tasks.
- Low-power mobile dongles replace SDRs with 10 Mbps throughput and 90% lower power consumption.
- The system validates real-time control using E2 interfaces and xApps in a live RAN environment.

## Abstract

Open Radio Access Networks (O-RAN) offer a flexible RAN architecture for future 6G systems, yet their complexity and lack of real-world testbeds pose interoperability challenges, particularly with emerging software platforms and robotic systems. Here we present a real-world software-defined radio testbed based on an open-source 4G long-term evolution (LTE) system, integrated with the near-real-time (Near-RT) RAN Intelligent Controller (RIC) via standard O-RAN E2 interfaces. It enables connectivity with robotic end devices such as a haptic controller and robotic arm, demonstrating the activation of E2 functionality within a live RAN environment. The testbed enables haptic operation with sub-one-second latency and block error rate (BLER) under 12% for tasks such as dental inspection use cases. We also demonstrate replacement of software-defined radios (SDRs) with low-power mobile dongles, achieving comparable 10 Mbps throughput while cutting power consumption by 90%. This setup establishes a foundation for advancing research and integration in managing next-generation RANs.

Saber Hassouna and colleagues demonstrate a complete, reproducible open radio access networks (O-RAN) architecture for low-latency teleoperation using xApps and system radio access network. The results validate robust control under real-time conditions.