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AirStack 0.2.0 Release Notes


06 December 2019

The Deepwave Digital team is proud to announce that AirStack Version 0.2.0 is now available for download to AIR-T customers.

Revision 0.2.0 of AirStack saw a number of changes and additional features designed to better support the underlying hardware and to make upgrades easier in the future. We have the end goal of making the AIR-T not just a development board, but a system that can be readily deployed to the field. Without further ado, here is the list of changes in AirStack 0.2.

New Features

  • In Place Firmware Upgrades - Firmware can now be updated directly from the Tegra SOM itself. There is no longer a need for an external PC to be hooked up via JTAG. After upgrading to 0.2.0, all users will be able to upgrade using a simple command line tool.
  • Variable Sample Rates - Improved sample rate decimation logic to allow for various sample rates. Currently the decimation logic supports dividing the base sample rate of 125 MSPS by 1, 2, 4, 8, or 16. We have added the necessary software hooks to integrate the new firmware decimation logic with SoapySDR. The supported sample rates can be obtained by calling listSampleRates().
  • Simplistic Software Upgrading - Software libraries critical to the functionality of the AIR-T are now properly Debian packaged. This will allow us to deploy fixes to specific components without needing a whole new OS image.
  • External LO - The tuning frequency of the AIR-T can now be set by an external oscillator. This adds the capability to phase align multiple AIR-T units for MIMO and many other applications.
  • 10 MHz Phase Locking - The AIR-T can now be phase locked to an external frequency reference enabling coherent processing across multiple units.
  • Live Frequency Tuning - The tuning frequency of the AIR-T may now be changed in real-time.
  • TX2i Support - We have implemented and tested our support for the industrial grade NVIDIA Jetson TX2i allowing for improved temperature ranges, vibration tolerance, and environmental conditions.
  • JetPack 4.2.2 - The OS image is now based upon NVIDIA JetPack SDK 4.2.2. This updates various GPU accelerated libraries as well as the kernel itself. Full highlights of these changes can be found here.
  • CUDA NVIDIA's CUDA has been upgraded to 10.0.326.
  • TensorRT NVIDIA's TensorRT has been upgraded to 1.
  • Ubuntu 18.04.2 - The operating system has been upgraded from Ubuntu 16.04.
  • Python Support For DNN Optimization - With the upgrade to JetPack 4.2.2, trained deep neural networks (DNN) may now be optimized and deployed solely using Python.
  • Docker Support - Support has been added for building and running Docker containers on the AIR-T.
  • Open Source Upgrades - We have updated our open source libraries, including GR-Wavelearner and GR-CUDA so that they are fully supported by AirStack 0.2.0.

Bug Fixes


  • Fixed JESD sync issue where occasionally the AIR-T would not synchronize.

Operating System

  • Fixed issues in order to properly enable the SPI bus on J21, thus allowing for control of external devices.


  • Various device driver fixes were implemented to ensure compatibility with newer Linux kernels.
  • Fixed various compatibility issues with GNU Radio, including adding the capability to dynamically change various RF settings.


The AIR-T upgraded software and firmware are available for customers to download in the Developer Portal.

We are in the process of updating and improving our tutorials to provide example code on how to utilize the new software functionality.

[1] Trained networks saved as .plan files on an AirStack 0.1 AIR-T will have to be re-optimized from the source UFF models to be compatible with AirStack 0.2.0 and later.

Last update: September 27, 2021