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Prototyping O-RAN Enabled UAV Experimentation for the AERPAW Testbed

Joshua Moore, Aly Sabri Abdalla, Charles Ueltschey, Vuk Marojevic

TL;DR

Through a series of aerial experiments, FlexRIC, an open-source RAN Intelligent Controller, is evaluated within the AERPAW hardware-software platform for network data monitoring, providing valuable insights into the proposed integration and revealing opportunities for leveraging O-RAN to create custom service based optimizations for cellular connected UAVs.

Abstract

The Open Radio Access Network (O-RAN) architecture is reshaping the telecommunications landscape by enhancing network flexibility, openness, and intelligence. This paper establishes the requirements, evaluates the design tradeoffs, and introduces a scalable architecture and prototype of an open-source O-RAN experimentation platform within the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW), an at scale testbed that integrates unmanned aerial vehicles (UAVs) with advanced wireless network technologies, offering experimentation in both outdoor testbed and emulation via a custom digital twin (DT). Through a series of aerial experiments, we evaluate FlexRIC, an open-source RAN Intelligent Controller, within the AERPAW hardware-software platform for network data monitoring, providing valuable insights into the proposed integration and revealing opportunities for leveraging O-RAN to create custom service based optimizations for cellular connected UAVs. We discuss the challenges and potential use cases of this integration and demonstrate the use of a generative artificial intelligence model for generating realistic data based on collected real-world data to support AERPAW's DT.

Prototyping O-RAN Enabled UAV Experimentation for the AERPAW Testbed

TL;DR

Through a series of aerial experiments, FlexRIC, an open-source RAN Intelligent Controller, is evaluated within the AERPAW hardware-software platform for network data monitoring, providing valuable insights into the proposed integration and revealing opportunities for leveraging O-RAN to create custom service based optimizations for cellular connected UAVs.

Abstract

The Open Radio Access Network (O-RAN) architecture is reshaping the telecommunications landscape by enhancing network flexibility, openness, and intelligence. This paper establishes the requirements, evaluates the design tradeoffs, and introduces a scalable architecture and prototype of an open-source O-RAN experimentation platform within the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW), an at scale testbed that integrates unmanned aerial vehicles (UAVs) with advanced wireless network technologies, offering experimentation in both outdoor testbed and emulation via a custom digital twin (DT). Through a series of aerial experiments, we evaluate FlexRIC, an open-source RAN Intelligent Controller, within the AERPAW hardware-software platform for network data monitoring, providing valuable insights into the proposed integration and revealing opportunities for leveraging O-RAN to create custom service based optimizations for cellular connected UAVs. We discuss the challenges and potential use cases of this integration and demonstrate the use of a generative artificial intelligence model for generating realistic data based on collected real-world data to support AERPAW's DT.

Paper Structure

This paper contains 13 sections, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. O-RAN Enabled UAV Research Platform
  3. Requirements
  4. Near-RT RIC Deployment Options for AERPAW
  5. Experimental Data Collection, Generation, and Analysis
  6. Average Data Rate Versus Distance
  7. Resource Block Allocation
  8. Service Data Unit Latency
  9. Advanced DT for Data Generation Leveraging O-RAN
  10. O-RAN Integration Challenges and R&D Opportunities
  11. O-RAN Integration Challenges
  12. O-RAN R&D Opportunities
  13. Conclusions

Figures (5)

  • Figure 1: System model (top) and sequence of events in the O-RAN reference architecture (bottom).
  • Figure 2: Experimental deployment showing the gNB and AUE.
  • Figure 3: Average data rates for a fixed ground UE and AUE at selected UAV hovering positions. The ground base station is at the origin.
  • Figure 4: RB allocation, achieved DL data rate, and SDU latency over horizontal distance to the gNB for a AUE flying at a continuous speed of 10 m/s (no ground UE in this experiment).
  • Figure 5: Measured (black) and generated (red and yellow) throughput over horizontal distance between the AUE and the gNB for different maximum PDSCH reference signal power parameter values set in the OAI configuration for the B210 Universal Software Radio Peripheral.