Table of Content

Open Access iconOpen Access

ARTICLE

crossmark

Intelligence-based Channel Equalization for 4x1 SFBC-OFDM Receiver

Divneet Singh Kapoor1,*, Amit Kumar Kohli2

1 Electronics and Communication Engineering Department, Chandigarh University, Mohali-140413, Punjab, India.
2 Electronics and Communication Engineering Department, Thapar Institute of Engineering and Technology, Patiala-147001, India.

* Corresponding Author: Divneet Singh Kapoor, email

Intelligent Automation & Soft Computing 2020, 26(3), 439-446. https://doi.org/10.32604/iasc.2020.013920

Abstract

This research paper represents an intelligent receiver based on the artificial-neuralnetworks (ANNs) for a 4x1 space-frequency-block-coded orthogonal-frequencydivision-multiplexing (SFBC-OFDM) system, working under slow time-varying frequency-selective fading channels. The proposed equalizer directly recovers transmitted symbols from the received signal, without the explicit requirement of the channel estimation. The ANN based equalizer is modelled by using feedforward as well as the recurrent neural-network (NN) architectures, and is trained using error backpropagation algorithms. The major focus is on efficiency and efficacy of three different strategies, namely the gradient-descent with momentum (GDM), resilient-propagation (RProp), and Levenberg-Marquardt (LM) algorithms. The recurrent neural network architecture based SFBC-OFDM system is found to be an appropriate choice in terms of the low bit-error-rate performance, while using different quasi-orthogonal space-time block codes.

Keywords


Cite This Article

D. Singh Kapoor and A. Kumar Kohli, "Intelligence-based channel equalization for 4x1 sfbc-ofdm receiver," Intelligent Automation & Soft Computing, vol. 26, no.3, pp. 439–446, 2020.

Citations




cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2995

    View

  • 2041

    Download

  • 1

    Like

Related articles

Share Link