Speaker
Description
Software-defined radios (SDRs) are widely used for wireless communication applications involving data, voice, and image transmission. A less common but increasingly relevant application is precise timing, where accurate synchronization between geographically separated locations is required. Although high-precision timing systems are typically based on expensive SDR platforms equipped with external frequency and pulse-per-second (PPS) synchronization inputs, recent work has demonstrated that the low-cost HackRF One SDR can also be adapted for precise time-transfer applications through firmware extensions. These extensions introduce timing capabilities that are absent in the standard device, including synchronized sampling, time-scale management, and fine clock-frequency adjustment.
This work focuses on the evolution of the software driver required to access and exploit these new timing functions. The first implementation extended the original HackRF driver and a corresponding Python wrapper through conventional manual software development. While functional, this architecture required continuous maintenance because every modification to the firmware or driver interface had to be replicated in the wrapper layer. To overcome these limitations, a new driver was developed within the SoapySDR framework, which provides a generalized SDR interface and native Python bindings.
The development of the new driver was strongly supported by artificial intelligence (AI) programming agents. Rather than specifying the timing extensions in detail, the development prompt referenced existing repositories containing both the original HackRF driver and its manually extended version. The AI agent was instructed to integrate the timing extensions into the existing SoapySDRHackRF driver while maintaining a modular code structure. Using this approach, a fully functional SoapySDR driver was generated within minutes and required only limited debugging and refactoring.
The results indicate that AI-assisted development can significantly accelerate the implementation of SDR drivers, reducing development effort by more than an order of magnitude. In addition to improving productivity, the resulting software architecture simplifies maintenance and enables broader adoption of low-cost SDR platforms for precision timing applications.
| Talk Length | N/A |
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| Link to Open Source Code | https://github.com/fabriziop/hackrf-htime , https://github.com/fabriziop/SoapyHackRFHTime |
| Acknowledge | Acknowledge In-Person |