We are pinch-me-proud to announce the release of AirStack Core 2.4.0! This is a major update packed with features to power new use cases on Deepwave’s RF AI system.
Whether you’re building direction finding applications or streaming communications waveforms, this release has something under the hood to make your development work more efficient and impactful.
Note: This release is specifically for our AIR7310 and AIR7311 models. If you are using earlier hardware models, you should continue using AirStack Core 1.0.
Let’s dive into what’s new!
What’s New in 2.4.0?
Phase Calibration
This is a big one. All channels can now be phase-aligned using a new AirStack Core register API. This means the Deepwave RF AI platform can support direction finding, beamforming, and other phase-critical applications. To help kick-start your development work, we’ve included a new tutorial that walks through computing phasors and configuring your AIR Transceiver (AIR-T): Receiver Phase Calibration on the AIR-T.
TX Transmit Queue
This AIR-T board support package release also provides more control for scheduling transmissions. New TX enhancements make transmitting communications waveforms much easier. Say goodbye to manually zero-padding buffers or writing scripts to copy all your samples into a single massive buffer. Developers can now schedule multiple timed transmissions, allowing for numerous buffers to be queued up for transmitting at different times in the future. Additionally, buffers can now be appended to one another using subsequent calls to writeStream() along with the SOAPY_SDR_END_BURST flag (check out our updated Transmit Tutorial for the code), thus creating a single continuous transmission.
JetPack 6.2.2 Upgrade
We’ve bumped the AirStack Core operating system baseline up to NVIDIA JetPack 6.2.2. This is a foundational upgrade for your signal processing pipelines. Integrating JetPack 6.2.2 into AirStack Core provides enhanced AirStack Core operating system stability, the latest JetPack security patches, and updates for common libraries such as cuDNN, CUDA, and TensorRT.
Secure Upgrade Tooling
We’ve also removed dependencies on NVIDIA’s native scripts for flashing and upgrading the AIR-T. While the process looks the same on your end, this feature set was enhanced and will provide human-readable logs and network security compliance for many corporate/government environments.
Resolved Issues & Polish
We’ve also squashed some bugs and optimized the hardware interactions:
- Clocking Fixes: AirStack Core will no longer reset your AIR-T clock source every time a new application is launched. This means you don’t have to wait to re-acquire GPS or external locks every time you run a new app on the AIR-T. We’ve also made the lock acquisition timeout user-configurable.
- Faster Device Creation: We’ve updated the RFIC reset logic to prevent resetting the AD9371 if it’s already in reset. Skipping these redundant steps saves time and resources when initializing your AIR-T.
- TX LO Calibration: We’ve enabled additional TX calibrations that reduce Local Oscillator (LO) leakage.
- RX Firmware Overflow Reporting: In previous versions, overflow conditions in the firmware’s buffers happened silently. Now, AirStack Core can diagnose and report firmware overflows. (Note: This usually happens when maxing out all channels at near-peak sample rates. We’re actively investigating further optimizations for a future release, but for now, you’ll receive the proper warnings).
How to Upgrade
If you’re running compatible hardware, we recommend upgrading by flashing (factory resetting) your device with the new 2.4.0 build.
- Download the new software build from the Developer Portal.
- Use the included airstack_core_installer GUI to run the update.
- For step-by-step instructions, check out the AirStack Core Installation Guide.