An advanced neuromorphic accelerator on FPGA for next-G spectrum sensing

TR Number

Date

2024-04-10

Journal Title

Journal ISSN

Volume Title

Publisher

Virginia Tech

Abstract

In modern communication systems, it’s important to detect and use available radio frequencies effectively. However, current methods face challenges with complexity and noise interference. We’ve developed a new approach using advanced artificial intelligence (AI) based computing techniques to improve efficiency and accuracy in this process. Our method shows promising results, requiring only minimal additional resources in exchange of improved performance compared to older techniques.

Description

Keywords

Field Programmable Gate Array, Hardware accelerator, On-Chip learning, Artificial intelligence, Recurrent Neural Network, Spike-Time-Dependent-Plasticity, Cognitive-Radio-Network, Spectrum Sensing

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