StormWave: An Open-Source Portable SDR Platform for Over-the-Air Resilience Evaluation of Terrestrial and Aerial Communications

This paper introduces StormWave, an open-source, portable software-defined radio platform designed to generate and monitor RF interference for realistic field evaluations of wireless communication resilience, demonstrating its effectiveness through ground and aerial experiments that reveal distance-dependent signal degradation under active interference.

The Gist

Imagine you are trying to have a quiet conversation with a friend in a park, but someone keeps shouting different types of noise at you to see how well you can still understand each other. That is essentially what the StormWave platform does, but instead of people talking, it uses radio waves to test how well wireless devices (like drones or cell phones) can handle interference.

Here is a simple breakdown of what the paper claims:

What is StormWave?

Think of StormWave as a "Swiss Army Knife for Radio Noise."

• Portable: It fits in a rugged case about the size of a large suitcase and weighs about as much as a heavy dog (50 lbs). One person can carry it to a field.
• Open-Source: The "recipe" (code) for building it is free for anyone to use and improve.
• Smart: It doesn't just make one type of noise. It can instantly switch between many different types of radio interference, from simple beeps to complex, wide-spectrum static.

How Does It Work?

The system is built like a high-tech command center with four main parts:

1. The Brain: A powerful mini-computer (Intel NUC) that runs the show.
2. The Speakers: Two radio devices (called USRPs) that act as the "mouths." One is dedicated to shouting the interference, and the other is a "listener" that constantly checks the radio spectrum to see what's happening.
3. The Power: A built-in battery system that lets it run for hours in the middle of a field without needing an outlet.
4. The Dashboard: A screen and keyboard that let the operator see everything in real-time, like a pilot's cockpit, showing exactly what kind of noise is being sent and how the target device is reacting.

The "Magic" Feature: Instant Switching

The most impressive thing StormWave can do is switch its "voice" instantly.
Imagine a DJ who can switch from playing a slow jazz song to a heavy metal track and then to a siren sound in the blink of an eye—so fast that the music never actually stops. StormWave can switch between different interference patterns in less than a microsecond (a millionth of a second). This allows researchers to test how a device handles a sudden change in noise without the device even realizing the test has changed.

What Did They Test?

The team took StormWave out into the real world to see how it performed in two main scenarios:

1. Ground Tests (The "Busy Street" Scenario)

• The Setup: They placed a transmitter and receiver 25 meters apart in a cluttered area with buildings and trees (which creates "echoes" or multipath effects). StormWave stood nearby, shouting interference.
• The Result: They found that the type of noise mattered. Simple noise didn't hurt much, but complex, wide-spectrum noise (like a chaotic storm) caused the connection to drop significantly. They also found that the "echoes" in the environment made the interference much worse, especially for complex signals.

2. Air-to-Air Tests (The "Flying Drone" Scenario)

• The Setup: They put the transmitter and receiver on drones flying in the sky while StormWave stayed on the ground. They flew the drones at different distances (from 20 meters to 100 meters away).
• The Result:
  • Close Range: When the drones were close (20–40 meters), the interference was devastating. The "conversation" between the drones became garbled and unstable.
  • Far Range: As the drones flew further away (60–100 meters), the interference became less effective, and the connection stabilized.
  • The Takeaway: The system proved that distance is a powerful shield. When the drones were close, the noise dominated; when they were far, the noise faded away.

Why Does This Matter?

The paper claims that StormWave is a reliable, repeatable tool for researchers. Before this, testing how well radios handle interference often required expensive, fixed equipment or simulations that didn't match real life. StormWave allows scientists to:

• Test devices in real weather and real terrain.
• Switch interference types instantly to see how quickly a device can adapt.
• Collect data on exactly how a signal degrades, not just whether it fails.

In short, StormWave is a portable, open-source lab that lets engineers stress-test wireless systems in the real world to make sure they can keep working even when the radio spectrum gets messy.

Technical Summary

Technical Summary: StormWave – An Open-Source Portable SDR Platform for Over-the-Air Resilience Evaluation

Problem Statement
The validation of wireless communication system resilience against Radio Frequency (RF) interference requires the ability to generate reproducible, structured interference conditions in realistic environments. While algorithmic and simulation-based studies are prevalent, significant gaps exist between these theoretical models and field-based evaluations. Existing interference-generation platforms often suffer from limitations such as fixed or minimally configurable signal generation, lack of seamless runtime waveform switching, poor portability, and an inability to support user-defined waveform integration or multi-radio orchestration. Furthermore, practical considerations like environmental resilience and continuous operation in disconnected field environments are rarely addressed in current solutions.

Methodology and System Design
To address these gaps, the authors present StormWave, an open-source, portable, weatherproof, and low-cost Software-Defined Radio (SDR) platform designed for comprehensive, field-based evaluation. The system architecture is divided into hardware and software components:

• Hardware Architecture: The platform integrates four primary modules:

  • Onboard Computing: An Intel NUC (i7-class CPU, 32 GB RAM) serves as the central orchestration hub, supporting real-time waveform execution, spectrum monitoring, and remote access.
  • Programmable Radio Platforms: Two USRP devices (USRP B210 and USRP N210 with CBX daughterboard) provide frequency coverage from 70 MHz to 6 GHz. One unit is dedicated to interference transmission, while the other performs continuous spectrum monitoring. Both are controlled via the USRP Hardware Driver (UHD) to allow coordinated operation and dynamic role assignment without hardware restarts.
  • Power System: A CyberPower uninterruptible power supply (UPS) enables up to two hours of runtime in field conditions without external power.
  • Display System: A portable monitor and keyboard allow for local configuration and control in the absence of network connectivity.

• Software Architecture: The software employs a three-layer modular design:

  1. User Control Interface: A PyQt-based GUI that manages waveform selection, parameter configuration, real-time spectrum visualization, and power monitoring. It supports automatic device discovery and dynamic generation of configuration widgets via JSON metadata.
  2. Waveform Integration Layer: This layer allows for extensible interference waveform development. It supports two execution models: Direct GNU Radio Flowgraph Mode for complex, custom pipelines, and Composed Base-Chain Mode for lightweight class-based definitions that automatically integrate with shared signal-processing chains. New waveforms are validated and registered via metadata files.
  3. System Backend Layer: This layer handles low-level runtime operations, including device orchestration, waveform synthesis (supporting narrowband, wideband, and protocol-aware waveforms like HORNet, OFDM, and OTFS), and data logging.

Key Contributions
The paper introduces StormWave as a field-ready platform that bridges the gap between simulation and reality through several key capabilities:

• Seamless Runtime Switching: The system supports switching between heterogeneous interference profiles (e.g., narrowband to wideband) in sub-microsecond timeframes (measured gaps < 100 ns) without interrupting transmission or restarting hardware.
• Extensibility: Users can upload custom waveforms via Python implementations and JSON parameter descriptions, which are automatically validated and integrated into the control pipeline.
• Integrated Visualization and Control: The platform provides synchronized real-time spectrum monitoring and logging, reducing operator burden and configuration errors.
• Portability and Robustness: Designed for single-operator deployment, the system is housed in a weatherproof enclosure and includes an independent power system for disconnected field operations.

Experimental Results
The authors evaluated StormWave through ground-based and air-to-air (A2A) experiments:

• Ground Experiments:

  • Scenario 1 (Cluttered/Multipath): In a 25m link with 5m interference proximity, wideband waveforms (HORNet, OFDM, OTFS) caused periodic throughput collapses, while narrowband baselines had modest effects. Higher-order modulations (QPSK) suffered deeper degradation than BPSK in this environment.
  • Scenario 2 (Open Field): In a 40m link with 15m interference proximity, the environment was cleaner. Here, BPSK-based interference proved more effective than QPSK, causing consistent throughput suppression (60–70%). This suggests that reduced multipath effects shift dominance toward lower-order modulation interference.
  • Waveform Switching: Experiments confirmed transition gaps of approximately 64 ns between waveforms (e.g., Baseline to HORNet), validating the system's ability to perform rapid runtime reconfiguration.

• Air-to-Air (A2A) Experiments:

  • Conducted with airborne transmitters/receivers and a ground-based StormWave unit.
  • Metrics included Access-Symbol Error Rate (ASER) and Kullback-Leibler Divergence (KLD) derived from raw I/Q snapshots.
  • Results showed that at short distances (20–40 m), the link was highly unstable (ASER > 20–40%, KLD > 25 nats). As distance increased to 60–100 m, metrics converged to near-baseline levels (ASER < 5%, KLD ≈ 0), demonstrating that close-range interference dominance outweighs path-loss effects in this regime.

Significance and Claims
The authors claim that StormWave provides a flexible, extensible, and field-ready platform for systematically validating the interference resilience of wireless systems under realistic operating conditions. By releasing the source code to the community, the work aims to enable reproducible evaluation of interference resilience. The paper emphasizes that StormWave is not merely a signal generator but a comprehensive evaluation tool that supports both built-in and user-defined waveforms, seamless switching, and rigorous data collection in dynamic environments. Future work is noted to include extending the platform toward adaptive, learning-driven interference generation and enabling remote access via cloud-based testbeds like UnionLab.