Identification of the Number of Wireless Channel Taps Using Deep Neural Networks

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Jaradat A. M., Walid Elgammal K. W. M. A., ÖZDEMİR M. K., ARSLAN H.

19th IEEE International New Circuits and Systems Conference, NEWCAS 2021, Toulon, Fransa, 13 - 16 Haziran 2021, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/newcas50681.2021.9462770
  • Basıldığı Şehir: Toulon
  • Basıldığı Ülke: Fransa
  • Anahtar Kelimeler: Wireless channel, deep neural network, channel taps, channel impulse response, channel identification
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • İstanbul Medipol Üniversitesi Adresli: Evet

Özet

In wireless communication systems, identifying the number of channel taps offers an enhanced estimation of the channel impulse response (CIR). In this work, efficient identification of the number of wireless channel taps has been achieved via deep neural networks (DNNs), where we modified an existing DNN and analyzed its convergence performance using only the transmitted and received signals of a wireless system. The displayed results demonstrate that the adopted DNN accomplishes superior performance in identifying the number of channel taps, as compared to an existing algorithm called Spectrum Weighted Identification of Signal Sources (SWISS).