Title: A review of wireless channel estimation techniques: challenges and solutions

Authors: M.N. Drakshayini; Manjunath R. Kounte

Addresses: School of ECE, REVA University, Bangalore, Karnataka, India ' School of ECE, REVA University, Bangalore, Karnataka, India

Abstract: In wireless communication, the transmitted signal is subjected to distortion, noise, frequency shift, non-linear attenuation, fading, and so on due to the inherent nature of the physical characteristics of the channel. To compensate for these impairments, efficient and accurate Channel Estimation is an imperative requirement. In this review, Channel Estimation techniques available in the literature are selectively identified, analysed and evaluated. Channel Estimation methods can be broadly classified into two major divisions as 'Model-Based' and 'Deep Learning-Based'. Model-Based methods strive for block-wise optimisation. On the contrary Deep Learning-Based methods provide end-to-end optimisation irrespective of variations in the channel characteristics. The main objective is to reduce the computational overhead while improving the accuracy of the Channel Estimation under a diverse transmission and propagation environment. In this paper, we review the contributions of various authors in dealing with Channel Estimation for the application of Deep Learning techniques in Channel Estimation.

Keywords: deep learning; convolutional neural network; channel state information; channel estimation.

DOI: 10.1504/IJWMC.2022.126390

International Journal of Wireless and Mobile Computing, 2022 Vol.23 No.2, pp.193 - 203

Received: 05 Oct 2021
Received in revised form: 08 May 2022
Accepted: 02 Jul 2022
Published online: 24 Oct 2022 *

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