Joint modulation format/bit-rate classification and signal-to-noise ratio estimation in multipath fading channels using deep machine learning

@article{Khan2016JointMF,
  title={Joint modulation format/bit-rate classification and signal-to-noise ratio estimation in multipath fading channels using deep machine learning},
  author={F. Khan and C. Lu and A. Lau},
  journal={Electronics Letters},
  year={2016},
  volume={52},
  pages={1272-1274}
}
  • F. Khan, C. Lu, A. Lau
  • Published 2016
  • Computer Science
  • Electronics Letters
  • A novel algorithm for simultaneous modulation format/bit-rate classification and non-data-aided (NDA) signal-to-noise ratio (SNR) estimation in multipath fading channels by applying deep machine learning-based pattern recognition on signals’ asynchronous delay-tap plots (ADTPs) is proposed. The results for three widely-used modulation formats at two different bit-rates demonstrate classification accuracy of 99.8%. In addition, NDA SNR estimation over a wide range of 0−30 dB is shown with mean… CONTINUE READING
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