Reconfigurable intelligent surface (RIS) assisted wireless systems require accurate channel
state information (CSI) to control wireless channels and improve both the bandwidth and …

Recently, convolutional neural network (CNN)-based channel estimation (CE) for massive
multiple-input multiple-output communication systems has achieved remarkable success …

OFDM is a powerful modulation technique that efficiently transmits high-speed digital data
over frequency-selective fading channels. It divides the signal into multiple subcarriers, each …

Deep learning (DL) has emerged as an effective tool for channel estimation in wireless
communication systems, especially under some imperfect environments. However, even …

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), a
fundamental transmission scheme, promises high throughput and robustness against …

In this paper, we introduce a reservoir computing (RC) structure, namely, windowed echo
state network (WESN), for multiple-input-multiple-output orthogonal frequency-division …

We propose a deep-learning approach for the joint MIMO detection and channel decoding
problem. Conventional MIMO receivers adopt a model-based approach for MIMO detection …

This paper addresses the sparse channel estimation problem in multiple-input-multiple-
output orthogonal frequency-division multiplexing (MIMO-OFDM) systems from the …

Wireless channel estimation is one of the challenging problems in multiple input multiple
output orthogonal frequency division multiplexing (MIMO-OFDM) wireless systems. The …

This letter presents our initial results in deep learning for channel estimation and signal
detection in orthogonal frequency-division multiplexing (OFDM) systems. In this letter, we …