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Research Article |

Design of a Deep Learning based Intelligent Receiver for a Wireless Communication System

Author(s): Drakshayini M.N., Manjunath R. Kounte and Chaya Ravindra

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 12, Issue 1

Publisher : FOREX Publication

Published : 20 march 2024

e-ISSN : 2347-470X

Page(s) : 228-237

DOI: https://doi.org/10.37391/IJEER.120132

Abstract

In communication systems, deep learning techniques can provide better predictions than model-based methods when the hidden features of the problem are prone to deviating substantially from the formulated assumptions. Severe signal impairments due to multipath fading and higher channel noise levels degrade the performance of conventional receivers. To overcome this, a novel intelligent receiver based on a deep learning network is presented, achieving better performance in terms of reduced bit error rate than a standalone conventional receiver. The experimental result shows that the relative decrement in the symbol error ratio due to the proposed method is about 9 percent compared to the traditional receiver when the Rician channel fading is relatively high.

Keywords: Confusion matrix, Deep learning, intelligent receiver, Percentage training error, Rician flat channel, Symbol Error Ratio.




Drakshayini M.N.*, School of Electronics and Communication Engineering, REVA University, Bengaluru, India; Email: mndrakshayini@gmail.com

Manjunath R. Kounte, School of Electronics and Communication Engineering, REVA University, Bengaluru, India; Email: manjunath.kounte@gmail.com

Chaya Ravindra, School of Electronics and Communication Engineering, REVA University, Bengaluru, India; Email: chaya.ravindra@gmail.com

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Drakshayini M.N., Manjunath R. Kounte and Chaya Ravindra (2024), Design of a Deep Learning based Intelligent Receiver for a Wireless Communication System. IJEER 12(1), 228-237. DOI: 10.37391/IJEER.120132.