iWave has successfully implemented the PYNQ framework on its Zynq™ UltraScale+™ RFSoC System on Module (SoM), empowering developers to perform Python-based control and visualization for real-time signal processing applications. This integration bridges the gap between high-performance FPGA hardware and high-level software development, enabling rapid prototyping of wireless communication, software-defined radio (SDR), and RF signal analysis systems.
By combining the flexibility of PYNQ with the performance of the RFSoC architecture, users can leverage integrated multi-GSPS ADCs and DACs for real-time waveform generation, acquisition, and digital signal processing all from an intuitive Python environment.
What is PYNQ?
PYNQ (Python Productivity for Zynq) is an open-source framework developed by AMD that allows developers to design FPGA-based applications using Python instead of traditional hardware description languages (HDL).
Through Jupyter Notebooks, PYNQ provides an interactive development environment to control programmable logic, manage hardware peripherals, and visualize data in real time. Operating on an embedded Linux platform, PYNQ combines the Processing System (PS) running Python applications with the Programmable Logic (PL), where hardware acceleration is implemented.
This co-design approach enables developers to offload compute-intensive signal processing tasks to the FPGA fabric while maintaining high-level software control, drastically reducing development complexity and time.
Custom IP Development
PYNQ supports the creation of custom IP cores to expand hardware functionality. Designers can use Vivado or MATLAB/Simulink HDL Coder to create and verify new IPs, which can then be accessed directly from Python as part of a PYNQ overlay.
This seamless software-hardware interaction empowers rapid experimentation, efficient control, and real-time system customization ideal for evolving RF and communication applications.
PYNQ Board Support Package (BSP)
The PYNQ BSP for iWave’s RFSoC platform provides all essential components required to operate the PYNQ framework on custom hardware.
It supports dynamic bitstream loading, enabling users to switch FPGA configurations at runtime without rebooting. The BSP includes:
- Python APIs and libraries for PL/PS interaction through DMA and AXI interfaces
- A pre-configured Jupyter Notebook environment for application development and visualization
- Real-time signal capture, processing, and plotting capabilities
This integration allows users to experiment, process, and analyze live RF signals interactively making it an invaluable tool for high-performance edge application development.
Applications of PYNQ on RFSoC
The PYNQ-enabled RFSoC platform delivers a powerful foundation for developing, testing, and validating advanced digital signal processing and wireless communication systems. Its performance enables a broad range of applications, such as:
- Spectrum analysis
- Digital modulation schemes (BPSK, QPSK, etc.)
- Orthogonal Frequency Division Multiplexing (OFDM) systems
Each of these demonstrates the RFSoC’s ability to combine high-speed data conversion, low-latency processing, and efficient analog-digital interfacing.
- Spectrum Analyzer
The RFSoC integrates high-speed RF Data Converters (RF-ADCs and RF-DACs) that connect the analog and digital domains with minimal latency.
In the Spectrum Analyzer demo, RF-ADC channels capture input signals, which are processed in the PL and visualized in real time via the PS.
Using a DAC-to-ADC loopback, signals generated by the DAC (single-tone or modulated) are analyzed by the ADC. The interface displays the spectrum, enabling evaluation of frequency response, signal purity, and noise characteristics. Adjustable sampling rates and waterfall spectrograms offer deeper insights into time-varying spectral data.
- RFSoC Radio
The platform supports real-time digital modulation schemes like BPSK and QPSK, implemented through FPGA hardware acceleration with Python-based control.
- BPSK transmits one bit per symbol (two phase states).
- QPSK transmits two bits per symbol (four phase states).
The PL executes high-speed operations like data modulation and pulse shaping, while the PYNQ layer allows users to visualize, control, and analyze these signals in real time via Jupyter.
This approach simplifies learning, prototyping, and testing for modern RF and communication applications.
- Orthogonal Frequency Division Multiplexing (OFDM)
OFDM is a multi-carrier modulation technique used in modern communication systems like 4G LTE, 5G NR, and Wi-Fi. It splits data into multiple subcarriers transmitted in parallel, improving efficiency and resilience to interference.
On iWave’s RFSoC platform, the OFDM demo allows users to experiment with modulation schemes ranging from BPSK and QPSK to higher-order QAMs (up to 256-QAM).
This demonstrates the RFSoC’s ability to manage high-throughput, real-time, and low-jitter communication pipelines essential for next-generation wireless technologies.
The implementation of PYNQ on iWave’s Zynq UltraScale+ RFSoC SoM opens new possibilities for developers seeking to combine Python simplicity with FPGA-level performance. It empowers researchers, educators, and engineers to prototype and deploy RF and communication systems faster, with more flexibility and reduced complexity. By enabling direct Python-based access to high-speed RF data converters and programmable logic, iWave continues to make FPGA innovation more accessible transforming the way embedded signal processing and wireless communication systems are developed and tested.
iWave is a global leader in the design and manufacturing of FPGA System on Modules and ODM Design Services. With over 26 years of diverse experience in the FPGA domain and a strong design-to-deployment competence, iWave strives to transform your ideas into time-to-market products with reliability, cost, and performance balance.
Looking for more insights? Contact us at mktg@iwave-global.com.
