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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Digital Signal Processing

Background:

  • Graphics processing units (GPUs) offer parallel processing capabilities that can accelerate computationally intensive tasks.
  • Traditional CPU-based implementations of signal processing algorithms may present performance bottlenecks in high-data rate communication systems.

Purpose of the Study:

  • To implement and evaluate signal processing algorithms on a GPU for high-data rate communication receivers.
  • To demonstrate the real-time processing capabilities of GPU-accelerated algorithms for the FM radio band.

Main Methods:

  • Implementation of digital filters, multirate filters, numerically controlled oscillators, and multi-stage digital down converters on a GPU.
  • Testing the implemented algorithms using the 20 MHz wide FM radio band (88-108 MHz).
  • Evaluation of two receiver architectures: a single channel receiver and a filter bank channelizer.

Main Results:

  • GPU implementations of signal processing algorithms achieve superior performance compared to CPU-based methods.
  • Real-time processing of the FM radio band was successfully demonstrated on an NVIDIA GeForce GTX 1080 graphics card.
  • Both single channel receiver and filter bank channelizer architectures showed effective real-time operation.

Conclusions:

  • GPU acceleration is a viable and effective approach for enhancing the performance of signal processing in high-data rate communication receivers.
  • The implemented GPU algorithms and receiver structures are suitable for real-time applications, including radio signal processing.
  • This work highlights the potential of GPUs for advancing communication system design and performance.