Deep Learning Based Channel Estimation in Data Driven MIMO Receiver

Authors

  • Vimlesh Gour
  • Mr. Kamal Niwaria
  • Dr. Bharti Chourasia

Keywords:

OFDM, MIMO, Space Time Trellis Code, Frequency Index Modulation, Compressed Sensing (CS), Channel Estimation

Abstract

OFDM (orthogonal frequency division multiplexing) is a wireless network methodology that sends multiple data streams across a particular channel while effectiently handling inter-symbol interference and enhancing frequency band available. And since the antenna is sending signals, evaluating the noise in a noisy channel is essential. This research aims into compressed sensing (CS) as a way to improve throughput and BER performance by transmitting additional data bits within every subcarrier frame whilst still limiting detector unpredictability. The Neuro-LS methodology is used in this study to generate a soft trellis decoding algorithm through channel estimation. Trellis decoding performs better BER, and DNN relying channel estimation outperforms BER, according to the findings.

Author Biographies

Vimlesh Gour

Research Scholar

Sarvepalli Radhakrishnan University 
Bhopal, M.P. India

Mr. Kamal Niwaria

Assistant Professor

Sarvepalli Radhakrishnan University

Bhopal, M.P, India

Dr. Bharti Chourasia

Associate Professor

Sarvepalli Radhakrishnan University

Bhopal, M.P, India

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Published

2022-01-15

How to Cite

Gour, V. ., Niwaria, M. K. ., & Chourasia, D. B. . (2022). Deep Learning Based Channel Estimation in Data Driven MIMO Receiver. SMART MOVES JOURNAL IJOSTHE, 8(6), 25–29. Retrieved from https://ijosthe.com/index.php/ojssports/article/view/166

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