The concept of Software-defined radio is not new, it has been around for years. It is basically about moving complex signal handling over to a digital software platform via PCs and smart systems.
While we have seen Artificial Intelligence already been implemented in a host of applications like speech recognition, gaming and autonomous vehicles, we are yet to see it being adapted for software-defined radio or incorporated into an RF hardware solution. This is why Deepwave Digital, a hardware and software solutions provider, has taken it upon themselves to come up with a Software-defined Radio with deep-learning muscle, called AIR-T.
AIR-T is a board that combines both high-end hardware and RF deep learning for SDR. AIR-T is equipped with three signal processors: a NVIDIA Jetson TX2 for signal processing and deep learning applications, a Xilinx Artix 7 FPGA for real-time operations and integrated CPUs for I/O, hardware, and software applications. The system also has a dual-channel MIMO transceiver with two 100MHz RX channels and two 250MHz TX channels, along with a rich set of connecting options including GPS Sync via 1 PPS and 10MHz, Ethernet, Wi-Fi, Bluetooth, HDMI, USB 2.0/3.0, SATA, and high-speed digital I/O.
This versatile system can function as a highly parallel SDR, data recorder, or inference engine for deep learning algorithms. The embedded GPU allows for SDR applications to process bandwidths greater than 200 MHz in real-time.” says Deepwave. “The AIR-T also uses zero copy memory access to overcome the data transfer overhead typically associated with GPU processing.
Read more: AIR-T: WHEN ARTIFICIAL INTELLIGENCE MEETS WITH RADIO – TRANSCEIVER