Taimoor Islam, Author at ARA

Measurement Study of Dynamics and Liquid Data Transport in OneWeb LEO Satellite Networks

Authors: Evan Gossling, Owen Perrin, Daji Qiao, Hongwei Zhang

This work conducts a measurement study of the Eutelsat/OneWeb Low Earth Orbit (LEO) Satellite Network (LSN) using ARA’s backhaul OneWeb user terminal (UT). OneWeb has been an under-studied network, so we first conduct a measurement study of the OneWeb LSN from a user’s perspective, and then examine the potential benefits of liquid data transport to increase the reliability of LSNs, as some LSN deployments may observe up to 2% packet loss¹.

Our topology figure showcases ARA’s backhaul UT deployed on the rooftop of Iowa State University’s Wilson Residence Hall. Through ARA’s online portal1, we can run experiments from a Dell PowerEdge server directly attached to the OneWeb indoor unit (IDU). Additionally, we utilize a virtual machine (VM) from the Google Cloud Platform near Ashburn, Virginia.

The UT connects via the Ku band to the OneWeb satellite constellation. The connected satellite then connects back to OneWeb ground stations via the Ka band in a bentpipe fashion. These ground stations transmit to and from OneWeb points of presence (PoPs), which are larger data centers where traffic within the OneWeb network is peered with the wider Internet. The service-level agreement (SLA) for ARA’s OneWeb connection is 100 Mbps downlink and 20 Mbps uplink.

We experiment with liquid data transport over our existing OneWeb LSN and deploy both endpoints of the transport in our architecture between the ARA server on ISU campus in Ames, Iowa, and the Google Cloud VM at Ashburn, Virginia.

We examine the statistical performance of liquid data transport in comparison to the baseline transport of TCP with no added coding scheme (aside from any coding which OneWeb may internally utilize). Our results figure compares the performance of liquid data with that of un-encoded TCP with BBR and CUBIC congestion control algorithms. We examine a time series of transferring data at a target rate of 10 Mbps over the LSN, which is subject to an artificial loss rate of 1%.

This additive 1% loss is used to demonstrate the effectiveness of liquid data in instances where the LSN drops packets, as is possible with LSNs such as Starlink, and to a certain extent, OneWeb. Overcoming this packet loss is important due to the network requirements of real-time applications, of which such applications will incur performance degradation when retransmissions must be made, which is exasperated when using an LSN.

Our figure shows that the performance of CUBIC increases significantly when liquid data transport is utilized compared to without it. To better understand this, we can further analyze the cwnd shown in the figure. As we can see, the cwnd value never increases to a suitable quantity for CUBIC (with no coding) when consistent losses are experienced. Essentially, these loss-based congestion control mechanisms prevent any substantial growth of the cwnd. On the other hand, when a tunnel is established between the TCP sender and receiver by the liquid data transport, packet losses are overcome inside the tunnel using the redundant repair data generated by the erasure code, thus shielding the TCP endpoints. As a result, the cwnd remains around a constant high value that corresponds to the target data rate of 10 Mbps.

BBR’s performance is comparatively similar in both cases as BBR is a delay-based protocol and its model of the link is not drastically affected by these packet losses; not to the degree that CUBIC’s loss-based model is. However, as the loss rate increases, the amount of retransmissions BBR (with no coding) must make increases correspondingly², whereas liquid data transport is able to overcome the packet loss without incurring additional retransmissions. For the traces shown in Fig. 9, BBR with no coding incurs 1767 retransmissions throughout the trace to transmit the application data, while BBR with liquid data transport only experiences 81 retransmissions.

Using liquid data transport, packet losses are shielded from the TCP endpoints where the congestion control algorithm is executed. It also eliminates or significantly reduces the amount of packet retransmissions. Both factors allow for natural growth and steady-state moderation of the cwnd size, which, in turn, results in increased and stable throughput. Overall, we find that OneWeb generally fulfills its service-level agreements, and liquid data transport may be used to further increase the reliability of TCP flows over LSNs.

Check the full article here.

[1] F. Michel, M. Trevisan, D. Giordano, and O. Bonaventure, “A first look at starlink performance,” in Proceedings of the 22nd ACM Internet Measurement Conference, 2022, pp. 130–136.
[2] Y. Cao, A. Jain, K. Sharma, A. Balasubramanian, and A. Gandhi, “When to use and when not to use bbr: An empirical analysis and evaluation study,” in Proceedings of the Internet Measurement Conference, 2019, pp. 130–136.

At-Scale, Real-World srsRAN Experiments in ARA

ARA is pleased to announce new long-range and field-validated open-source 5G and open RAN capabilities using srsRAN across rural and agricultural environments. This large-scale, outdoor deployment demonstrates stable, reliable and high-throughput connectivity using programmable base stations and commercial-off-the-shelf (COTS) UEs. Leveraging high-power and low-noise amplifiers at the programmable base stations, ARA now supports over-the-air coverage up to 1.3km using NI N320 software-defined radios and Quectel RM500Q-GL UEs. Recent outdoor trials demonstrate stable attachment, high throughput, and robust link reliability, even in complex terrains such as valleys and cell edges—showcasing ARA’s ability to expose rich propagation diversity and realistic interference dynamics. Single-cell results shown in Figure 1 confirm strong throughput scaling with distance and terrain, while multi-cell trials reveal predictable patterns of throughput, latency, and jitter. Figure 3 shows reliability in terms of packet delivery rate in multi-cell interference scenarios. The setup for the results presented in Figure 3 is illustrated in Figure 2. These characteristics make ARA uniquely suited for benchmarking, optimization, and future 6G and Open RAN research in real-world conditions.

Beyond connectivity, ARA’s srsRAN deployment enables end-to-end measurement, prototyping, and multi-cell experimentation across distributed UE sites and multi-sector gNBs. Researchers can capture per-UE and per-packet metrics—such as throughput, packet delivery reliability, latency, jitter, and interference effects at kilometer-scale ranges. The ARA platform thus enables rigorous exploration of URLLC, HRLLC, multi-UE contention, rural macro-cell behavior and interference modeling under rich outdoor channel conditions leveraging srsRAN software stack. With such capabilities, ARA is well positioned as one of the few living labs to directly support the mission of the Linux Foundation Open Centralized Unit Distributed Unit (OCUDU) initiative by providing a large-scale, field-deployed and fully programmable open RAN platform that accelerates open-source ecosystem adoption, reduces reliance on proprietary infrastructure, and enables rigorous next-generation wireless research and prototyping in strategic agricultural and rural settings. Example experiments can be conducted by following the detailed ARA user manual.

*Figure 1: Multi-UE downlink throughput*

*Figure 2: Multi-Cell deployment scenario*

*Figure 3: Packet delivery rate in multi-cell interference scenarios*

ARA December 2025 Newsletter Is Now Live!

We’re excited to share that the December 2025 ARA Newsletter is now available! This edition highlights ARA milestones, community insights, and the newest capabilities unlocked through the ARA wireless living lab. Highlights of this edition include:

Join us in September 2026 for AraFest 26! Co-located with the 2026 Farm Progress Show, AraFest’26 will showcase breakthroughs in advanced wireless technologies. Please join us to co-shape AraFest’26. Talks, panels, and demos are all welcome! 
ARA capability update: A Starlink terminal has been installed next to the OneWeb user terminal. More experiments are supported by ARA , such as outdoor srsRAN experiments and OAI experiments at new outdoor sites.
User stories of how ARA can be used for 1) field scouting acceleration in precision agriculture and 2) random access reliability enhancement for NextG.

“Amiga”: Accelerating Field Scouting with ARA’s FutureG Connectivity

In the AIIRA national AI institute, Prof. Soumik Sarkar (Mechanical Engineering) and Prof. Asheesh “Danny” Singh (Agronomy) at Iowa State University leverages ARA to investigate how networked agricultural ground vehicles, remote sensing and computing, and machine learning can automate labor-intensive field scouting—transforming hours of manual assessment into near-real-time analysis and decision-making.

Traditional field scouting and crop phenotyping are both time-consuming and labor-intensive. To address this challenge, the team is developing an integrated platform (shown in the picture below) that combines a highly customized, field-deployable “Amiga” platform (Bonsai Robotics, San Jose, CA), which can be equipped with a wide range of sensors such as high-resolution imaging sensors, with an automated navigation system, an ARA communication user endpoint, and a high-performance computing unit. Together, these components enable automated data collection, fast model training, and data-driven actuation decisions directly in the field.

The ARA wireless living lab plays a key role in this initiative. The custom ARA communication endpoint developed for the Amiga robot delivers the throughput, coverage, reliability, and low latency needed for real-time video streaming, data collection, and edge inference, which is in sharp contrast to the unstable and intermittent connectivity commonly experienced in rural farm fields today. Joscif Raigne, a PhD student who manages and operates the Amiga experimental platform, shared his enthusiasm: “The sky is the limit for agricultural applications when unmanned vehicles, field sensors, and computing servers are interconnected through next-generation, reliable, high-performance networks.”

The Amiga platform was featured as a plenary demo at AraFest’24. Videos of the presentation and demonstration can be found here. Currently, the team is expanding the pilot to include other types of unmanned agricultural vehicles, such as scouting drones and sprayer drones, for precision weed control and other farm applications.

Enhancing NextG Random Access Reliability in Programmable Wireless Living Labs

The Center for Wireless, Communities and Innovation (WiCI) at Iowa State University has taken a significant step forward in improving the coverage and reliability of next generation random access (RA) procedure with the development of AraRACH: Enhancing NextG Random Access Reliability in Programmable Wireless Living Labs. By leveraging real‑world data from the ARA wireless living lab, they devised a slot‑based scheduling framework that reschedules RA messages into full downlink and uplink slots, unlocking all 14 OFDM symbols for each message to overcome reliability issues in large‑scale outdoor 5G/6G deployments. This work was recently honored with the Best Paper Award at the 2025 IEEE International Conference on Network Softwarization (NetSoft), and this work has enabled ARA to become the first-of-its-kind living lab for supporting open-source, whole-stack programmability in end-to-end 5G research and innovation from UE to gNB and Core.

Open source 5G/6G software stacks such as OpenAirInterface (OAI) have unlocked unprecedented flexibility for 5G and next generation wireless research and innovation. However, at the core of this innovation is the performance in terms of coverage and reliability of these wireless living labs. For instance, interfacing power amplifiers and low noise amplifiers with software-defined radios (SDRs) for experimenting outdoors introduces issues in random access procedure—a process crucial in establishing connectivity between user equipment (UE) and the core network in 5G and 6G systems.

Particularly, open-source 5G software stacks like OAI are faced with two major random access (RACH) procedure challenges in real-world and large-scale deployments–timing and reliability. In terms of timing, the RACH procedure fails due to the lack of precise TDD synchronization between the software stack and the amplifier within the special slot (S). For instance, the default OAI DL-UL switching occurs at the end of the last DL slot. However, as shown in Fig.1, the DL to UL switching gap must follow the last DL symbol within the special slot. Consequently, msg2 (a DL message) which is scheduled in a special slot fails to be transmitted due to amplifier being in the receive/uplink mode at the start of the special slot. This consequently causes the RACH procedure to fail. Also shown in Fig.1, OAI by default leverage a few symbols within the special or mixed slot to schedule msg2 and smg3. For instance, 6 downlink symbols and 4 uplink symbols are used to schedule msg2 and msg3 respectively. Such configuration causes the RACH procedure to fail over longer UE-gNB distances, consequently affecting reliability. We present AraRACH to jointly tackle both timing and reliability issues related to open source 5G RACH procedure. As shown in Fig. 2, AraRACH schedules RA response message (msg2) with a full downlink slot and radio resource control (RRC) connection request message (msg3) with a full uplink slot, granting each message access to all 14 OFDM symbols. This approach solves the timing issue which exists in the special slot, improves message coding rates by leveraging more OFDM symbols, and eventually improves msg2 and msg3 reliability over longer distances and under varying channel conditions.

Fig.1: Default msg2 and msg3 scheduling in special slots

Fig. 2: Leveraging full DL and UL slots for msg2 and msg3

The ARA wireless living lab played a pivotal role in validating AraRACH. Spanning a 30 km‑diameter area in central Iowa and consisting of 7 software-defined radio gNBs and 30 UEs, including deployments in crop and livestock farms, grain bins, residential and industrial sites, ARA allowed real‑world experiments in both line‑of‑sight (LoS) and non‑LoS (nLoS) conditions. Researchers provisioned radio and compute resources via the ARA Portal and launched containerized OAI experiments for reproducible and scalable trials.

Results demonstrated that AraRACH extends reliable 5G connection over unprecedented ranges: successful UE attachments were achieved at distances exceeding one mile, the longest to date using open‑source 5G software stacks on a programmable wireless living lab. Msg2 reception probability exceeded 90% whenever scheduled with at least eight to nine OFDM symbols, while msg3 reception probability remained above 80% even at one‑mile ranges when allocated eleven or more symbols.

By proving end‑to‑end, open‑source 5G research and prototyping is viable in large‑scale outdoor environments, AraRACH lays a blueprint for improving the performance of open source 5G, 6G and open RAN field deployments worldwide. Future work will focus on automating SLIV selection based on in-situ channel conditions, extending the approach to emerging 6G RA schemes, releasing the AraRACH datasets and code to foster community-driven reproducibility, and contributing the source code of AraRACH back to the OpenAirInterface open-source community.

Author’s Background

Joshua Ofori Boateng is a Ph.D. candidate in Computer Engineering at Iowa State University and a graduate researcher at the Center for Wireless, Communities and Innovation (WiCI), where he works under Profs. Hongwei Zhang and Daji Qiao on the ARA platform. He co‑designed the ARA wireless living lab testbed, contributing to publications such as “Design and Implementation of ARA Wireless Living Lab for Rural Broadband and Applications” and “AraSDR: End‑to‑End, Fully‑Programmable Living Lab for 5G and Beyond.” Joshua holds a bachelor’s degree in Telecommunications Engineering from Kwame Nkrumah University of Science and Technology, Ghana, and his research focuses on open‑source NextG wireless platforms, Open RAN, and virtualization of software-defined radio platforms. To date, he has published 10 peer‑reviewed papers and has over 100 citations.

Author: Joshua Ofori Boateng

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