Deepwave and RAPIDS Team Collaborate on cuSignal 0.13 Over the past few months NVIDIA has been working on a new version of cuSignal: version 0.13. As part of their RAPIDS environment, cuSignal GPU accelerates all of the signal processing functions in the SciPy Signal Library. Read the Medium full article here. Online Processing Deepwave has […]
Deepwave Digital Webinar Update The webinar on March 25, 2020 was a great success and we thank you for attending! The video stream, slides, and source code are now available to the general public. Slides You may download the slides here. Video Stream Source Code Available in the new webinar section of our […]
Power Spectrum Measurement If you are looking for a very simple way to acquire the power spectral density of a received signal with the AIR-T, you may like the Soapy Power Project. The resulting spectrum output may be used for monitoring interference, acquiring signals for deep learning, or for examining a test signal. Soapy Power […]
06 December 2019 Major Upgrades to the AIR-T 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 […]
Deepwave’s AIR-T Shows Viability as CBRS Sensor Deepwave Digital is proud to announce that their sensor has concluded certification testing to become a critical component in the 5G Citizens Broadband Radio Service (CBRS) network: the first commercial spectrum sharing network. The Deepwave team has implemented a deep neural network on their Artificial Intelligence Radio Transceiver […]
End-to-End Signal Processing and Deep Learning Using Embedded GPUs The following presentation was given at NVIDIA’s GPU Technology Conference (GTC) in Washington, DC on November 5, 2019. It was a great event where technology was showcased from many different research areas. Presenter Daniel Bryant Abstract We’ll present the GPU-accelerated digital signal processing (DSP) applications enabled […]
The Premier AI Event is back in DC "The center of the AI ecosystem shifts to D.C. this fall, when the GPU Technology Conference arrives at the Reagan Center in Washington, from Nov. 4-6." Check out the full NVIDIA Blog post here. The GTC DC event is a top-tier AI conference directed towards government, defense, […]
Overview This tutorial will teach you how to integrate GPU processing using CUDA with GNU Radio on the AIR-T software defined radio. Once completed, you will be able to build a custom GPU processing block within GNU Radio and use it to process your own signals. The tutorial assumes some familiarity in programming in Python […]
FFTs with CUDA on the AIR-T with GNU Radio GPUs are extremely well suited for processes that are highly parallel. The Fast Fourier Transform (FFT) is one of the most common techniques in signal processing and happens to be a highly parallel algorithm. In this blog post the Deepwave team walks you though how to […]
AIR-T Enclosures Fresh off the Production Line We have just received our first production versions of the new AIR-T software defined radio enclosure and it is beautiful. If you already have and AIR-T, you can order a kit today to protect your SDR. If you are thinking about acquiring our GPU enabled SDR, make sure […]
Title: Simplifying AI for Communications, Radar, and Wireless Systems Presented by John Ferguson (CEO Deepwave Digital) Abstract Radio frequency (RF) systems have become increasingly complex, and the number of connected devices is expected to increase. We’ll discuss how deep learning within RF shows promise for dealing with a congested spectrum by enhancing reliability and simplifying […]
Deepwave Digital directly enables the incorporation of artificial intelligence (AI) in radio frequency (RF) and wireless systems by supplying customers an integrated hardware and software solution. Our technology moves the AI computation engine to the signal edge of the RF system to reduce network bandwidth, latency, and human-driven analysis requirements.