Related papers: Underwater Acoustic Channel Adaptive Estimation us…
The notion of low-noise channels was recently proposed and analyzed in detail in order to describe noise-processes driven by environment [M. Hotta, T. Karasawa and M. Ozawa, Phys. Rev. A72, 052334 (2005)]. An estimation theory of low-noise…
A main challenge faced in the deep learning-based Underwater Image Enhancement (UIE) is that the ground truth high-quality image is unavailable. Most of the existing methods first generate approximate reference maps and then train an…
Pixel-based fluid antennas provide enhanced multiplexing gains and quicker radiation pattern switching than traditional designs. However, this innovation introduces challenges for channel estimation and analog precoding due to the…
This paper investigates the robust wideband channel estimation problem in the millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In such a scenario, the beam squint effect that the array response vectors vary…
Underwater imaging plays a pivotal role in marine exploration and ecological monitoring. However, it faces significant challenges of limited transmission bandwidth and severe distortion in the aquatic environment. In this work, to achieve…
Navigation and source localization in the undersea environment are challenged by the absence of a ubiquitous positioning system. Passive acoustic ranging offers a valuable means of obtaining location information underwater. We present a…
In cognitive radio systems, employing sensing-based spectrum access strategies, secondary users are required to perform channel sensing in order to detect the activities of primary users. In realistic scenarios, channel sensing occurs with…
This paper focuses on the problem of separately modulating and jointly estimating two independent continuous-valued parameters sent over a Gaussian multiple-access channel (MAC) under the mean square error (MSE) criterion. To this end, we…
Compressed sensing aims at reconstructing sparse signals from significantly reduced number of samples, and a popular reconstruction approach is $\ell_1$-norm minimization. In this correspondence, a method called orthonormal expansion is…
Data transmission over the mmWave in fifth-generation wireless networks aims to support very high speed wireless communications. A substantial increase in spectrum efficiency for mmWave transmission can be achieved by using advanced hybrid…
Gaussian quantum channels are relevant operations in continuous variable systems. In general, given an arbitrary state, the action on it is well-known provided that the quantum channels are completely characterized. In this work, we…
In this paper, we present a deep learning (DL) algorithm for channel estimation in communication systems. We consider the time-frequency response of a fast fading communication channel as a two-dimensional image. The aim is to find the…
Large-scale multiple-antenna systems have been identified as a promising technology for the next generation of wireless systems. However, by scaling up the number of receive antennas the energy consumption will also increase. One possible…
Underwater optical wireless technologies offer multiple advantages over the acoustic technology. Acoustic signals, for instance, are susceptible to noise from marine sources due to marine life and human activities. This is not the case with…
Recent studies indicate that the noise characteristics of phasor measurement units (PMUs) can be more accurately described by non-Gaussian distributions. Consequently, estimation techniques based on Gaussian noise assumptions may produce…
Broadband wireless channel is a time dispersive and becomes strongly frequency selective. In most cases, the channel is composed of a few dominant coefficients and a large part of coefficients is approximately zero or zero. To exploit the…
This paper proposes a joint channel and data estimation (JCDE) algorithm for uplink multiuser extremely large-scale multiple-input-multiple-output (XL-MIMO) systems. The initial channel estimation is formulated as a sparse reconstruction…
Underwater acoustic target recognition is critical for maritime applications, yet it faces challenges arising from the complex and diverse nature of ship-radiated noise. To address these issues, we propose a robust deep learning-based…
Channel estimation is a fundamental task in communication systems and is critical for effective demodulation. While most works deal with a simple scenario where the measurements are corrupted by the additive white Gaussian noise (AWGN),…
Estimation is a critical component of synchronization in wireless and signal processing systems. There is a rich body of work on estimator derivation, optimization, and statistical characterization from analytic system models which are used…