Name
Title | ||
|---|---|---|
FPGA Based High-Throughput Real-Time Feature Extraction for Modulation Classification |
Abstract | ||
|---|---|---|
The spectral correlation density (SCD) function is a feature extraction method used in signal classification systems. Due to its computational complexity, SCD has not been a desirable method for systems under power and real-time constraints. In this study, we present results for a hardware implementation of key kernels of the SCD function on a Field Programmable Gate Array (FPGA). By analyzing profiling results for a state of the art GPU implementation, we developed a preliminary architecture that is able to accelerate the most computationally demanding aspects of the SCD algorithm. We find that this FPGA architecture is able to achieve a 2.03X speedup relative to state of the art GPU-based SCD implementations by coupling SCD's large-scale data-parallel nature with an architecture well suited for fine-grained control flow and data access patterns. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/FCCM48280.2020.00073 | 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM) |
Keywords | DocType | ISSN |
modulation classification,spectral correlation density function,signal classification systems,computational complexity,real-time constraints,SCD function,field programmable gate array,GPU,FPGA architecture,real-time feature extraction,fine-grained control flow,data access patterns | Conference | 2576-2613 |
ISBN | Citations | PageRank |
978-1-7281-5804-4 | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joshua Mack | 1 | 1 | 2.40 |
| Ali Akoglu | 2 | 157 | 29.40 |