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Free space optical (FSO) communications using orbital angular momentum (OAM) modes has recently received a considerable interest. Propagating OAM modes through free space may be subject to atmospheric turbulence (AT) distortions that cause…
Deep learning (DL) has proven its unprecedented success in diverse fields such as computer vision, natural language processing, and speech recognition by its strong representation ability and ease of computation. As we move forward to a…
Federated learning (FL) as a promising edge-learning framework can effectively address the latency and privacy issues by featuring distributed learning at the devices and model aggregation in the central server. In order to enable efficient…
Since the invention of the laser in the 60s, one of the most fundamental communication channels has been the free-space optical channel. For this type of channel, a number of effects generally need to be considered, including diffraction,…
In the era of advanced technologies, mobile devices are equipped with computing and sensing capabilities that gather excessive amounts of data. These amounts of data are suitable for training different learning models. Cooperated with…
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…
Machine learning (ML) has been widely applied to the upper layers of wireless communication systems for various purposes, such as deployment of cognitive radio and communication network. However, its application to the physical layer is…
The implementation of efficient free-space channels is fundamental for both classical and quantum Free-Space Optical (FSO) communication. This can be challenging for fibre-coupled receivers, due to the time variant inhomogeneity of the…
This paper presents an innovative approach to enhancing machine learning based communication systems, specifically focusing on multiple-input multiple-output (MIMO) configurations using autoencoders. We optimize the transmitter, receiver,…
In this paper, we propose a novel free-space optical (FSO) communication system utilizing optical skyrmions. We introduce a scheme referred to as skyrmion number modulation (SkM), which employs index modulation by encoding information onto…
Free-space optical (FSO) channel offers line-of-sight wireless communication with high data rates and high secrecy utilizing unlicensed optical spectrum and also paves the way to the solution of the last-mile access problem. Since…
Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space optical networks. This paper investigates the optimal design…
Due to the relatively high cost of deploying optical fibers, free space optical (FSO) links have been developed as a cost-effective alternative technology for next generation cellular networks. However, in order to have a practical role in…
Atmospheric turbulence poses a significant challenge to the performance of object detection models. Turbulence causes distortions, blurring, and noise in images by bending and scattering light rays due to variations in the refractive index…
Coherent detection can provide enhanced receiver sensitivity and spectral efficiency in free-space optical (FSO) communications. However, turbulence can cause modal power coupling effects on a Gaussian data beam and significantly degrade…
Federated learning (FL) is a novel machine learning setting that enables on-device intelligence via decentralized training and federated optimization. Deep neural networks' rapid development facilitates the learning techniques for modeling…
The integration with artificial intelligence (AI) is recognized as one of the six usage scenarios in next-generation wireless communications. However, several critical challenges hinder the widespread application of deep learning (DL)…
In recent years, free space optical communication has gained significant importance owing to its unique features: large bandwidth, license-free spectrum, high data rate, easy and quick deployability, less power and low mass requirements.…
Modeling of turbulent flows is still challenging. One way to deal with the large scale separation due to turbulence is to simulate only the large scales and model the unresolved contributions as done in large-eddy simulation (LES). This…
Automatic modulation recognition (AMR) detects the modulation scheme of the received signals for further signal processing without needing prior information, and provides the essential function when such information is missing. Recent…