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Spiking Neural Networks for Detecting Satellite-Based Internet-of-Things Signals
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  • Kosta Dakic ,
  • Bassel Al Homssi ,
  • Sumeet Walia ,
  • Akram Al-Hourani
Kosta Dakic
RMIT University

Corresponding Author:[email protected]

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Bassel Al Homssi
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Sumeet Walia
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Akram Al-Hourani
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Abstract

The obtained results demonstrate a significantly enhanced detection performance under heavy interference conditions when employing spiking-based and deep learning detection techniques, as opposed to traditional baseline matched-filter methods. Although spiking-based detection approaches exhibit error rates comparable to those of deep learning techniques, they consume considerably less power -- several orders of magnitude lower, in fact. Owing to their power efficiency, spiking-based detection networks emerge as the optimal choice for signal detection in resource-limited systems, such as low-Earth orbit satellites.