FPGA-Accelerated Decision Tree Classifier for Real-Time Supervision of Bluetooth SoC
| Autor: | Abdelrahman Elkanishy, Abdel-Hameed A. Badawy, Youssef Aly, Derrick T. Rivera, C. P. Michael, Paul M. Furth |
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| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Decision tree learning Feature extraction 020206 networking & telecommunications 02 engineering and technology law.invention Bluetooth law Hardware_INTEGRATEDCIRCUITS 0202 electrical engineering electronic engineering information engineering Wireless 020201 artificial intelligence & image processing Transceiver Field-programmable gate array business Communications protocol Computer hardware Block (data storage) |
| Zdroj: | ReConFig |
| DOI: | 10.1109/reconfig48160.2019.8994784 |
| Popis: | Wireless communication protocols are used in all smart devices and systems. This work proposes an FPGA-accelerated supervisory system that classifies the operation of a communication system-on-chip (SoC). In this work, the selected communication protocol is Bluetooth (BT). The input supply current to the transceiver block of the SoC is monitored and sampled at 50 kHz. We extract simple descriptive features from the transceiver input power signal and use them to train a machine learning (ML) model to classify two different BT operation modes. We implemented ADC sampling, feature extraction, and a real-time decision tree classifier on an Intel MAX 10 FPGA. The measured classification accuracy is 97.4%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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