In this letter, we propose a deep learning-assisted approach for signal detection in uplink
orthogonal frequency-division multiplexing (OFDM) systems over time-varying channels. In …

In various practical orthogonal frequency-division multiplexing (OFDM) systems, the
estimation accuracy at the receiver is challenging, and, specifically when operate over time …

For real‐time transmission of high‐bandwidth sensor data from an unmanned aircraft
vehicle (UAV) to the ground station (GS) in an unmanned aircraft system, a high‐speed …

In this paper, we propose a deep learning aided approach for signal detection in orthogonal
frequency-division multiplexing (OFDM) systems with time-varying channels. The method …

The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple
access (O-NOMA) systems that are caused by signals that overlap and interfere with each …

This paper presents an adaptive algorithm for unbiased estimation of autoregressive
Rayleigh flat fading parameters in OFDM systems. To this end, a variable leaky steepest …

The performance of an Orthogonal Frequency Division Multiplexing (OFDM) system to
transmit high bandwidth data from a vehicle to a base station can suffer from Inter-Carrier …

In this study, four channel‐estimation (CE) methods are proposed for sparse high mobility
doubly selective channels. These methods are designed to take advantage of the sparsity of …

This paper deals with optimal power allocation for channel estimation of orthogonal
frequency‐division multiplexing uplinks in time‐varying channels. In the existing literature …

Orthogonal frequency division multiplexing (OFDM) scheme increases bandwidth efficiency
(BE) of data transmission and eliminates inter symbol interference (ISI). As a result, it has …