The benefits of end-to-end learning has been demonstrated over AWGN channels but has
not yet been quantified over realistic wireless channel models. This work aims to fill this gap …

This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in
the context of linear inverse problems with additive Gaussian noise. We fit a GMM to given …

In this paper, we present a channel estimation approach based on deep learning to solve
the problem that the orthogonal frequency division multiplexing (OFDM) system channel …

Abstract Multiple-Input Multiple-Output (MIMO) communication System-Orthogonal
Frequency Division Multiplexing (OFDM) approach can produce reliable transmission of …

We propose an innovative machine learning-based technique to address the problem of
channel acquisition at the base station in frequency division duplex systems. In this context …

Accurate channel estimation and allocation are vital in the provision of reconfigurable
intelligent surfaces (RIS)-aided wireless network services to mobile users. Typically, channel …

In wireless communication systems, channel estimation is one of the vital processes for
determining channel characteristics. Deep learning based approaches construct a 2D image …

This letter presents a deep learning (DL) algorithm for compensating the impacts of phase
noise in channel estimation and data detection for multicarrier systems. The proposed DL …

Utilising the dispersed resources that are accessible inside a cluster, the dispersed Deep
Learning System (DDLS) is able to successfully complete the process of training complex …

The advanced Internet of Things (IoT) technique has provided a promising vision in
emergency response issues with its convenience in environment cognition and …