FIR (Finite Impulse Response) filters are at the heart of many FPGA-based DSP systems, including wireless transceivers, radar, medical imaging, and audio processing. They are widely used because of their stability (always bounded output), linear phase response (preserving waveform shape), and flexibility in designing sharp cutoffs or custom frequency responses. FIR filters help remove unwanted frequency components or shape the spectral response of a signal, making them essential in practical DSP applications.
Traditionally, FIR filters can be implemented directly in RTL using multiply-accumulate pipelines, but this requires significant development time. Xilinx’s FIR Compiler IP provides a ready-made, optimized solution using FPGA DSP48 slices, supporting large tap counts and flexible configuration through Xilinx Vivado tool.
In this blog, we walk through configuring and integrating the Xilinx FIR Compiler IP into a Vivado project for high-performance signal processing in FPGA. Included is a practical implementation using MATLAB-generated coefficients and multi-tone DDS signals.
FIR Compiler Overview
The Xilinx FIR Compiler IP supports:
- Single-rate, decimation, and interpolation modes
- Reloadable or fixed coefficients
- Fully pipelined architectures for high Fmax
- AXI4-Stream interface for streaming DSP pipelines
- Optional AXI4-Lite interface for runtime coefficient reload
Common Use Cases
- Channel filtering in wireless systems
- Anti-aliasing before decimation
- Equalization filters in communications
- Audio processing
Figure 1: FIR Compiler System Architecture
A FIR (Finite Impulse Response) filter processes input signals by multiplying recent input samples with fixed coefficients and summing the results. Its architecture mainly consists of delay elements, multipliers, and adders arranged in a chain
System Architecture Overview
Key Components:
- Zynq PS: Processing System for control and data generation
- FIR Compiler (PL): High-speed filtering in hardware
- AXI DMA / custom AXI4-Stream source-sink: Move data in/out of the FIR
- AXI4-Stream interfaces: Continuous streaming of samples
Communication Interfaces
- AXI4-Stream: High-speed, handshake-based data movement
- AXI4-Lite: Optional control interface for runtime coefficient reloading
Design Steps and Work Implementation
Step 1: Open Vivado Project
- Created a new RTL project in Vivado.
- Selected target FPGA device (e.g., ZCU102).
Step 2: Add FIR Compiler IP
- Opened the IP Catalog.
- Added Xilinx FIR Compiler to the block design.
Step 3: Configure FIR Compiler
- Filter Type: Single-rate
- Number of Taps: 64 (as per filter requirements)
- Coefficient Width: 16 bits (fixed-point design)
- Implementation: Fully pipelined using DSP48 slices
- Interface: AXI4-Stream for input/output
Step 4: Generate FIR Coefficients in MATLAB
- Designed a low-pass FIR filter with:
- Sampling frequency (FsF_sFs) = 100 MHz
- Passband = 1 MHz
- Stopband = 5 MHz
- Generated coefficients in MATLAB.
- Imported coefficients directly into FIR Compiler IP in vector mode, bypassing the COE file method. This ensures accurate MATLAB-to-FPGA behavior.
Step 5: DDS Signal Integration
- Configured two DDS sources in Vivado:
- DDS 1: 2 MHz output
- DDS 2: 15 MHz output
- Summed the two DDS outputs to form a composite input signal.
- Connected this composite waveform to the FIR Compiler input.
Highlights of the Work
- Real-time filtering of multi-tone signals using FIR Compiler IP.
- MATLAB-generated coefficients are loaded directly in vector mode, enabling flexible and accurate filtering.
- Demonstrates high-speed FIR implementation suitable for FPGA DSP applications.
The design begins with two DDS Compilers, each generating a digital signal at a different frequency. One produces a 2 MHz tone, while the other generates a 15 MHz tone. These two signals are then combined in an Adder/Subtracter block to form a single mixed waveform containing both frequency components.
This combined signal is processed by the FIR Compiler, which applies digital filtering to isolate the desired frequency. The filter ensures that unwanted components are suppressed, leaving a clean output. A Clocking Wizard provides the stable clock required for synchronization, while a Utility Vector Logic block manages enable and acknowledge signals to maintain smooth data flow across the system.
Simulation and Verification
- Stimulated FIR with composite DDS signals (2 MHz + 15 MHz).
- Verified FIR output matches MATLAB simulation results.
- Confirmed correct attenuation in stopband and accurate passband response.
The system operates with a 100 MHz clock and generates two signals, one at 2 MHz and the other at 15 MHz. These signals are combined to form a composite waveform, which is then passed through a low-pass filter. The filter effectively removes the higher-frequency component, leaving only the 2 MHz signal at the output.
Performance Tips
- Use symmetric coefficients to reduce multipliers.
- Increase pipeline stages for higher clock speeds.
- Optimize coefficient scaling to prevent overflow.
- Keep data width minimal without losing precision.
FIR Filters Reduce Development Time
By integrating MATLAB-generated FIR coefficients and DDS multi-tone signals, this project demonstrates high-speed FIR filtering on FPGA using the Xilinx FIR Compiler IP. Leveraging vector-mode coefficients, AXI4-Stream, and FPGA DSP slices enables real-time, low-latency, high-throughput filtering.
This approach significantly reduces development time compared to RTL-only implementations and provides an accurate, scalable workflow for advanced DSP applications in communications, radar, and audio processing.
Next Blog Topic: Understanding AXI-Stream Interfaces for DSP Data Pipelines.
Read all the blogs in the DSP Building Blocks series.