With the advent of machine learning, there has been renewed interest in the problem of
wireless channel estimation. This paper presents a novel low-complexity wireless channel …

In this paper, we consider joint estimation of the channel length and of the impulse response
for OFDM systems, exploiting information criteria to find the best trade-off, in terms of …

Deep learning (DL) has exhibited notable effectiveness in channel estimation for orthogonal
frequency division multiplexing (OFDM) systems. However, most existing neural networks …

In the area of wireless communication, channel estimation is a challenging problem due to
the need for real-time implementation as well as system dependence on the estimation …

Using deep learning technologies, the channel estimate for an orthogonal frequency
division multiplexing system (OFDM) based on pilots is done in this work. To be more …

Knowledge of the channel over which signals are sent is of prime importance in modern
wireless communications. Inaccurate or incomplete channel information leads to high error …

In this paper, we devise a highly efficient machine learning-based channel estimation for
orthogonal frequency division multiplexing (OFDM) systems, in which the training of the …

The limited time available for acquiring the channel state in mobile broadband wireless
communication systems makes it crucial to count with channel estimation methods that attain …

Channel state estimation (CSE) is essential for orthogonal frequency division multiplexing
(OFDM) wireless systems to deal with multipath channel fading. To attain a high data rate …

Modern communication systems are based on orthogonal frequency division multiplexing
(OFDM). They are designed for dealing with frequency selective channels considering …