AI-Based Spectrum Sensing with Nvidia Jetson and USRP

Application Note Number and Authors

AN-811

Authors

Bharat Agarwal and Neel Pandeya

Executive Summary

This application note presents a complete framework for real-time spectrum sensing using NI Universal Serial Radio Peripheral (USRP) Software-Defined Radios (SDRs) and NVIDIA Jetson or standard x86 compute platforms. The framework is not limited to a single USRP model—the X410, X310, and B2xx series (e.g., B206) can all be used as transmitters or receivers depending on the deployment scenario. The solution leverages the NI-RF Data Recording API to enable scalable RF data acquisition, SigMF-compliant metadata tagging, and seamless integration with machine learning workflows.

The document outlines three core usage scenarios:

1. x86-Based Development Workflow: Using a workstation or server-class x86 machine, paired with high-end USRPs such as the X410 or X310, the system supports wideband spectrum sensing (up to 400 MHz instantaneous bandwidth per channel). This configuration is ideal for laboratory development, algorithm training, and high-throughput dataset generation.
2. Jetson-Based Embedded Sensing (Primary Use Case): Using an NVIDIA Jetson platform as the host (e.g., AGX Orin) with a compact B206 SDR as receiver and an X410 as transmitter, the system delivers efficient edge inference with GPU acceleration. Although the B206 limits the instantaneous bandwidth to 56 MHz, this configuration emphasizes portability, low power, and real-time embedded operation.
3. User-Defined Dataset Integration: In addition to live spectrum sensing, the framework supports integration and generation of user-defined datasets. This functionality extends the applicability of the system beyond real-time capture, enabling flexible experimentation, reproducibility, and seamless AI/ML dataset preparation. Two complementary capabilities are supported:
   1. SigMF Dataset Recording
      • All captured RF data is stored in the Signal Metadata Format (SigMF).
      • SigMF pairs raw IQ samples (.sigmf-data) with a corresponding metadata file (.sigmf-meta) in JSON format.
      • Metadata describes acquisition parameters such as frequency, bandwidth, gain, device type, timestamps, and scenario context.
      • Being human-readable and portable, SigMF datasets can be used across a wide range of software environments, making them ideal for wireless research, spectrum monitoring, AI/ML training for 6G, and regulatory validation.
      • Example: A spectrum sensing session at 3.5 GHz, 20 MHz bandwidth, and 10-second duration will result in a SigMF-compliant dataset ready for further processing or ML-based classification.
   2. Continuous Waveform Playback with User-Defined Files
      • The platform supports continuous transmission and replay of user-defined waveforms in TDMS or MATLAB (.mat) formats.
      • This allows testing with standard-compliant signals such as 5G NR, LTE, Radar, or Wi-Fi, or custom-designed waveforms.
      • By replaying predefined waveforms, researchers can benchmark algorithms, validate coexistence scenarios, and reproduce experiments consistently across testbeds.
      • Example: A MATLAB-generated LTE downlink frame can be continuously transmitted via an X410 while a B206 or X310 records the received signal in SigMF format for classification.

Together, these capabilities ensure that the NI-RF Data Recording API can handle both dataset creation (SigMF-based recording) and waveform-driven experimentation (TDMS/MAT playback), thereby covering the entire pipeline from signal generation to ML-ready dataset production.

By combining NI's reliable SDR hardware with NVIDIA's efficient edge compute platforms and a unified data interface, this solution supports a wide range of spectrum intelligence applications—from interference detection and dynamic spectrum access to embedded RF analytics. The methodology enables scalable deployment from lab to field, supporting real-time insights and long-term data collection in a streamlined, modular pipeline.

USRP B206 Overview

The USRP B206 is a compact, low-cost SDR developed by NI / Ettus Research. It supports full-duplex operation with one transmit and one receive channel, making it ideal for a variety of wireless communication and sensing applications. The B206 covers a wide RF frequency range from 70 MHz to 6 GHz and supports up to 56 MHz of instantaneous bandwidth. This makes it suitable for applications such as spectrum sensing, dynamic spectrum access, and cognitive radio.

The device connects to a host system via a high-speed USB 3.0 interface, which enables data rates sufficient for wideband real-time signal acquisition and transmission. It also supports USB 2.0 with reduced performance. The B206 includes a Xilinx Spartan-6 FPGA for onboard signal processing and is powered either through USB or an external DC supply, the latter being preferred for optimal RF performance.

The USRP B206 is compatible with both x86 and ARM-based hosts, including embedded platforms like the NVIDIA Jetson series. This enables portable and energy-efficient deployment of spectrum sensing pipelines at the network edge. It is fully supported by the open-source UHD and integrates with popular SDR development tools such as GNU Radio, MATLAB, and LabVIEW.

Typical use cases for the B206 include real-time spectrum monitoring, wireless signal classification using machine learning, prototyping of 4G/5G systems, and SDR education and training. Its compact size and flexible software support make it an excellent choice for both laboratory research and embedded field deployments.

Key Features of the USRP B206:

• RF Capabilities: 1 TX, 1 RX, independently tunable, RF transceiver, 70 MHz to 6 GHz, up to 56 MHz bandwidth
• Programmable Logic: FPGA: Xilinx Spartan-6 XC6SLX150
• Software: UHD 4.9 or later, GNU Radio, C/C++ and Python
• Synchronization: REF (external 10 MHz or PPS reference)
• Digital Interfaces: USB 3.0, GPIO (8 I/O lines with 3.3 V I/O voltage), and JTAG
• Power, form factor: 5 V DC, 0.9 A maximum; Board-only: 84.3 mm × 51.0 mm × 8.7 mm; Enclosed: 84.9 mm × 55.7 mm × 19.8 mm

Executive Summary

Overview

This Application Note presents ...