FPGA-Accelerated Signal Processing

Overview

This project focuses on implementing high-performance signal processing algorithms on Field-Programmable Gate Arrays (FPGAs) for real-time applications. By leveraging the parallel processing capabilities of FPGAs, we achieve significant speedups compared to traditional CPU-based implementations.

Key Features

• Ultra-low latency: Sub-microsecond processing times
• High throughput: Processing millions of samples per second
• Flexible architecture: Easily adaptable to different signal processing tasks
• Energy efficient: Optimized for performance per watt

Technical Implementation

Hardware Platform

• FPGA: Xilinx Zynq UltraScale+ MPSoC
• Development Board: ZCU104 Evaluation Kit
• Interface: AXI4-Stream for high-speed data transfer

Signal Processing Algorithms Implemented

1. Fast Fourier Transform (FFT)

• Radix-2 and Radix-4 implementations
• Configurable transform sizes (256 to 4096 points)
• Pipelined architecture for continuous data streaming

2. Digital Filtering

• FIR filters with up to 256 taps
• IIR filters (Butterworth, Chebyshev, Elliptic)
• Adaptive filtering using LMS and RLS algorithms

3. Spectral Analysis

• Power spectral density estimation
• Spectrogram computation
• Real-time spectrum analyzer

Performance Metrics

Applications

This FPGA-accelerated signal processing platform has been successfully deployed in:

1. Software-Defined Radio (SDR)
   • Real-time demodulation and decoding
   • Wideband spectrum monitoring
2. Biomedical Signal Processing
   • ECG and EEG analysis
   • Real-time anomaly detection
3. Financial Data Analysis
   • High-frequency trading signals
   • Market microstructure analysis

Code Structure

fpga-signal-processing/
├── hdl/
│   ├── fft/
│   ├── filters/
│   └── interfaces/
├── hls/
│   ├── adaptive_filter/
│   └── spectral_analysis/
├── software/
│   ├── drivers/
│   └── applications/
└── testbench/
    ├── unit_tests/
    └── system_tests/

Getting Started

Prerequisites

• Xilinx Vivado 2023.2 or later
• Vitis HLS for high-level synthesis
• Python 3.8+ for host applications

Building the Project

# Clone the repository
git clone https://github.com/muditbhargava66/fpga-signal-processing.git

# Build the hardware
cd fpga-signal-processing
make hw

# Build the software
make sw

# Run tests
make test

Future Work

• Implementation of machine learning inference engines
• Support for multiple FPGA platforms
• Integration with cloud-based FPGA services
• Real-time visualization interfaces

Publications and Presentations

• “High-Performance Signal Processing on FPGAs: A Practical Approach” - In preparation
• Workshop presentation at FPGA Developer Forum 2024

Acknowledgments

This project builds upon excellent open-source FPGA libraries and tools. Special thanks to the Xilinx community and contributors to open-source HDL projects.