Examination of the Non-Orthogonal Multiple Access System Using Long Short Memory Based Deep Neural Network

Authors

  • Ravi Shankar Madanapalle Institute of Technology & Science, Madanapalle, India https://orcid.org/0000-0001-7532-3275
  • T. V. Ramana Chitkara University school of Engineering and Technology, Chitkara University, Himachal Pradesh, India
  • Preeti Singh UIET, CSJM University, Kanpur, India
  • Sandeep Gupta JECRC University, Jaipur, Rajasthan, India
  • Haider Mehraj Baba Ghulam Shah Badshah University, Rajouri, J&K, India

DOI:

https://doi.org/10.13052/jmm1550-4646.18214

Keywords:

NOMA, recurrent neural network, QPSK, RNN, deep neural network

Abstract

This paper investigates deep learning (DL) non-orthogonal multiple access (NOMA) receivers based on long short-term memory (LSTM) under Rayleigh fading channel circumstances. The performance comparison between the DL NOMA detector and the traditional NOMA method is established, and results have shown that the DL-based NOMA detector performance is far better in comparison with conventional NOMA detectors. Simulation curves are compared with the performance of the DL detector in terms of minimum mean square estimate (MMSE) and least square error (LSE) estimate, taking all realistic circumstances, except the cyclic prefix (CP), and clipping distortion into account. The simulation curves demonstrate that the performance of the DL-based detector is exceptionally good when it equals 1 when the noise signal ratio (SNR) is more than 15 dB, assuming that the DL method is more resilient to clipping distortion.

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Author Biographies

Ravi Shankar, Madanapalle Institute of Technology & Science, Madanapalle, India

Ravi Shankar received his BE degree in Electronics and Communication Engineering from Jiwaji University, Gwalior, India, in 2006. He received his MTech degree in Electronics and Communication Engineering from GGSIPU, New Delhi, India, in 2012. He received a PhD in Wireless Communication from the National Institute of Technology Patna, Patna, India, in 2019. He was an assistant professor at MRCE Faridabad, from 2013 to 2014, where he was engaged in researching wireless communication networks. He is presently an assistant professor at MITS Madanapalle, Madanapalle, India. His current research interests cover cooperative communication, D2D communication, IoT/M2M networks and networks protocols. He is a student member of IEEE.

T. V. Ramana, Chitkara University school of Engineering and Technology, Chitkara University, Himachal Pradesh, India

T. V. Ramana is working as Professor in computer science and engineering, Chitkara University, Himachal Pradesh, India. He completed Ph. D in JNTUH, Hyderabad. His research interests include software engineering, computer system architecture, machine learning and IOT.

Preeti Singh, UIET, CSJM University, Kanpur, India

Preeti Singh, Assistant Professor, MSc.(Electronics), (UIET, CSJM, University, Kanpur), M.Tech. (Tezpur University), Area of Specialization: Digital Design & Technology/Antenna Design, Total experience: 8 Publications Conferences: 02.

Sandeep Gupta, JECRC University, Jaipur, Rajasthan, India

Sandeep Gupta, Assistant Professor, Electrical Engineering Department, JECRC University, Jaipur (Rajasthan), JECRC University, Jaipur (Rajasthan).

Haider Mehraj, Baba Ghulam Shah Badshah University, Rajouri, J&K, India

Haider Mehraj received his B.Tech in Electronics and Communication Engineering from the Guru Nanak Dev University, Amritsar, India in 2009 and M.Tech in Communication and Information Technology from National Institute of Technology, Srinagar, India in 2011. He is currently pursuing PhD in Biometrics at the National Institute of Technology, Srinagar, India and working as Assistant Professor in BGSB University, Rajouri, India. He has a number of national and international publications to his credit. His research interests include Biometrics, Image Processing, Deep Learning, and Pattern Recognition.

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Published

2021-11-16

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Articles