The AntSDR T510 AI Puts an AMD RFSoC and an NVIDIA Jetson on One Board

Modern wireless research requires a collection of specialized hardware working together. One device captures radio signals, another processes them, and yet another runs AI models to identify patterns or make decisions. While that approach works, it also creates new challenges. Moving massive amounts of data between systems can become a bottleneck, synchronization across multiple channels adds complexity, and every extra piece of hardware introduces additional latency. For applications like phased-array radar, massive MIMO, spectrum monitoring, and intelligent wireless sensing, getting data from the antenna to an actionable result isn’t easy.

The MicroPhase Technology AntSDR T510 AI was designed to bring all of those pieces together into one package. It combines an AMD RFSoC for real-time RF processing with an NVIDIA Jetson module for GPU-accelerated AI workloads, creating a platform that can acquire, process, analyze, and respond to wireless signals without relying on external systems. With support for eight synchronized transmit and receive channels, direct RF coverage from 1 MHz to 6 GHz, and onboard AI acceleration, the T510 AI is a complete edge computing platform for next-generation wireless development.

At the core of the system is an AMD Zynq UltraScale+ RFSoC ZU47DR, which integrates programmable logic, embedded processing, and high-speed RF data converters on a single chip. The platform provides eight 14-bit ADC channels capable of sampling at up to 5 GSPS and eight 14-bit DAC channels that reach 9.85 GSPS. It supports an 8T8R architecture with synchronized ADC and DAC operation, making it suitable for applications that depend on precise timing and phase alignment.

The RF subsystem handles signal acquisition and deterministic processing tasks such as digital upconversion, downconversion, interpolation, decimation, and multi-channel synchronization. Each channel supports up to 2 GHz of baseband bandwidth, allowing developers to work with wideband signals without requiring additional hardware.

While the RFSoC focuses on real-time signal processing, the integrated NVIDIA Jetson module handles computationally intensive workloads. These include AI inference, signal classification, spectrum analysis, feature extraction, and wireless environment perception. By keeping both subsystems on the same platform, developers can move directly from RF capture to intelligent analysis without streaming data to a separate workstation.

The T510 AI also includes features aimed at larger-scale deployments. Multiple boards can be synchronized together to expand beyond the onboard eight channels, enabling systems with 16, 32, or more synchronized RF paths. Timing options include external clock references, onboard OCXO or TCXO sources, GPS timing, and PPS trigger support.

The platform ships with Ubuntu 22.04 and CUDA preconfigured on the Jetson module. It also supports GNU Radio, SoapySDR, and an open driver framework called IQTAXI. Developers can build applications in Python or C++ and access the RF hardware through high-level APIs, reducing the need for FPGA development experience.

MicroPhase says it plans to release hardware references, firmware sources, host-side streaming examples, and Jetson AI workflow examples through a public GitHub repository. If you are interested in this board, be sure to sign up for notifications over at Crowd Supply.