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The 6G communication system will be designed at sub-THz frequencies due to increasing demand in data rates, emerging new applications and advanced communication technologies. These high-performing systems will heavily rely on artificial intelligence (AI) for efficient and robust design of transceivers. In this work, we propose a deep neural network (DNN) beamformer that will replace the use of phase shifters for a massive array of antenna elements employed at the ground station for wideband LEO satellite communication at sub-THz bands. We show that the signal processing algorithm employed using DNN is capable to match the performance of a true-time delay beamformer as the angle of arrival of the received wideband signal at the ground station is changing due to rapid movement of the LEO satellite. The implementation of DNN beamformer will be able to reduce the cost of receiver and provide a way for the efficient and compact design of the massive array beamforming for wideband LEO satellite applications.

The evolution of communication system to the next generation e.g. B5G and 6G demands an ultra-reliable performance regardless of weather conditions. Such ultra-reliable system design will require that that the effects of short-term adverse weather events on communication system has to be modelled more accurately so that system design should be dynamically adaptive to such events. The performance of satellite link is severely affected by dynamic rain attenuation and thus an accurate and reliable modelling of performance parameters is essential for dynamic fade countermeasures especially above 10 GHz. In this work, we model the energy per bit to noise spectral density ratio ($E_b/N_0$) using Gaussian Mixture (GM) model during rainy events. The developed mathematical expression is used to accurately model the bit error rate (BER), outage probability and channel capacity of the link. The average BER, upper bound on BER and average ergodic capacity of an M-ary phase shift keying scheme (MPSK) using the GM model of $E_b/N_0$ is derived to evaluate the performance of the link under such short-term weather impairments. We then show the numerical results and analysis using the GM model of the measured $E_b/N_0$ data obtained with AMoS-7 satellite at a site located in Israel.

The progress in quantum computing would make the traditional encryption methods easier to hack and hence the next generation of communication networks should include various cross-layer solutions to ensure the cybersecurity of network. In this work, we propose a physical layer solution that rely on taking advantage from the inherent physical properties of the channel that marks its imprint on the propagation of the electromagnetic signal through the stochastic atmospheric channel. The proposed architecture would ensure the cybersecurity of a ground station against an MITM attack launched from an aerial platform (AP). As the signal traverses through the channel, various atmospheric effects including thermal noise and tropospheric scintillation fading causes rapid fluctuations in the received signal. The signal at the ground station from a satellite and an AP would traverse different spatial path over the dynamic atmosphere and hence will show different noise like rapid variations at the ground station. These noisy variations are extracted from the received signal using wavelet filtering technique and processed through a deep neural network based on long-short term memory network (LSTM) to identify whether the incoming signal belong to a legitimate satellite or a spoofing AP. We show that an accuracy of more than $98 \%$ is achieved in the considered scenario with the proposed network architecture as the altitude of AP changes for launching a machine-in-the-middle (MITM) attack in the line-of-sight direction.

The increasing demand in data rates and new emerging applications require that the future generation of satellite networks will be designed at sub-THz frequencies with ultra-broad bandwidth. At such frequencies, the satellite channel is impaired by the highly frequency dependent absorption of the signal by the gaseous atmospheric media besides the thermal noise from the sky, the ground, receiver circuit and molecular absorption noise thus, making it a highly frequency-selective channel. In this work, we derive a theoretical upper bound on the channel capacity of a LEO satellite communication link by optimizing the power spectral density (PSD) of the transmitted signal considering the physicla aspects of THz channel. We obtain a closed form expression of optimum transmitted signal PSD that maximizes the channel capacity of LEO satellite link as the elevation angle changes with the transmitted power held constant.

6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are inaccurate, which results in an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently, we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10 mm/h), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. This will enable the design of more efficient systems, enabling design of an adaptive system that will adjust itself to rain conditions in such a way that performance will be improved. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more efficient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design.

6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are an inaccurate, which results with an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10mm/hr), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more effi-cient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design. Keywords: atmospheric propagation, communication system performance, attenuation, com-munication

In this paper, we present a novel approach, enabling the measurement of nitrate concentrations in natural soil porewater containing natural soil dissolved organic carbon (DOC). The method is based on UV absorbance spectroscopy, combined with fluorescence spectroscopy, for simultaneous analysis of DOC and nitrate concentrations. The analytical procedure involves deduction of the absorption caused by the DOC from the total absorbance in the UV range that is attributed to both DOC and nitrate in the water solution. The analytical concept has been successfully tested in soil water samples obtained from five agricultural sites, as well as in water samples obtained from a commercial humus soil mixture. We believe that the new analytical concept can provide a scientific foundation for developing a sensor for real-time nitrate concentration measurements in agricultural soils. As such, it can play a significant role in reducing nitrate pollution in water resources, optimizing input application in agriculture, and decreasing food production costs.

Diffuse optical tomography using deep learning is an emerging technology that has found impressive medical diagnostic applications. However, creating an optical imaging system that uses visible and near-infrared (NIR) light is not straightforward due to photon absorption and multi-scattering by tissues. The high distortion levels caused due to these effects make the image reconstruction incredibly challenging. To overcome these challenges, various techniques have been proposed in the past, with varying success. One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. This article attempts to provide researchers with the necessary background and tools to implement deep learning methods to solve diffuse optical tomography.

Lack of real-time information on nutrient availability in cultivated soils inherently leads to excess application of fertilizers in agriculture. As a result, nitrate, which is a soluble, stable, and mobile component of fertilizers, leaches below the root zone through the unsaturated zone and eventually pollutes the groundwater and other related water resources. Rising nitrate concentration in aquifers is recognized as a worldwide environmental problem that contributes to water scarcity. The development of technologies for continuous in situ measurement of nitrate concentration in soils is essential for optimizing fertilizer application and preventing water resource pollution by nitrate. Here we present a conceptual approach for a monitoring system that enables in situ and continuous measurement of nitrate concentration in soil. The monitoring system is based on absorbance spectroscopy techniques for direct determination of nitrate concentration in soil porewater without pretreatment, such as filtration, dilution, or reagent supplementation. A new analytical procedure was developed to improve measurement accuracy while eliminating the typical measurement interference caused by soil dissolved organic carbon. The analytical procedure was tested at four field sites over 2 years and proved to be an effective tool for nitrate analysis when directly applied on untreated soil solution samples. A soil nitrate-monitoring apparatus, combining specially designed optical flow cells with soil porewater-sampling units, enabled, for the first time, real-time continuous measurement of nitrate concentration in soils. Real-time, high-resolution measurement of nitrate concentration in the soil has revealed the complex variations in soil nitrate concentrations in response to fertigation pattern. Such data are crucial for optimizing fertilizer application and reducing pollution potential of groundwater.

The capability to increase the robustness to scattering has become a crucial request for communication protocols and imaging systems. Here we perform a complete analysis regarding the spatial features and the polarization of structured beams propagating in different scattering media. We observe different behaviors for structured light scattered by a solution of polystyrene latex beads in water and by tissue-mimicking phantom. The reported study can help in establishing a framework for the application of structured light illumination in imaging and diagnostic.

Reconstructing objects behind scattering media is a challenging issue with applications in biomedical imaging, non-distractive testing, computer-assisted surgery, and autonomous vehicular systems. Such systems’ main challenge is the multiple scattering of the photons in the angular and spatial domain, which results in a blurred image. Previous works try to improve the reconstructing ability using deep learning algorithms, with some success. We enhance these methods by illuminating the set-up using several modes of vortex beams obtaining a series of time-gated images corresponding to each mode. The images are accurately reconstructed using a deep learning algorithm by analyzing the pattern captured in the camera. This study shows that using vortex beams instead of Gaussian beams enhances the deep learning algorithm’s image reconstruction ability in terms of the peak signal-to-noise ratio (PSNR) by ~ 2.5 dB and ~1 dB when low and high scattering scatterers are used respectively.

This manuscript discusses the most relevant aspects of the practical implementation of a long-range Quantum Key Distribution (QKD) link with trusted nodes, achieving the highest possible secret key rate generation within the security and system-level constraints. To this purpose, it describes the implementation of an end-to-end QKD system, including implementation aspects from the physical transmission of photon states through a standard telecommunications grade optical fiber, to consideration of quantum metrology and information reconciliation protocols based on forward error correction codes. In addition, since there are circumstances when a fiber optical link may not be available, it examines the problems involved with the implementation of a Free Space Optics (FSO) QKD link. The manuscript also discusses the problem of information reconciliation in Continuous Variable (CV) QKD scenarios on FSO links, showing that in long distance links, since the sign of the received Gaussian samples contains the largest fraction of information, Unequal Error Protection (UEP) reverse reconciliation schemes can be designed. The presented results have been achieved within the NATO SPS project “Analysis, design and implementation of an end-to-end 400 km QKD link”.

A deep-learning algorithm is employed to detect simulated anomalies inside compressed breasts using near-infrared light. Anomaly detection is improved by 55% after employing the algorithm according to the Dice similarity coefficient.

Optical interrogation of tissues is broadly considered in biomedical applications. Nevertheless, light scattering by tissue limits the resolution and accuracy achieved when investigating sub-surface tissue features. Light carrying optical angular momentum or complex polarization profiles, offers different propagation characteristics through scattering media compared to light with unstructured beam profiles. Here we discuss the behaviour of structured light scattered by tissue-mimicking phantoms. We study the spatial and the polarization profile of the scattered modes as a function of a range of optical parameters of the phantoms, with varying scattering and absorption coefficients and of different lengths. These results show the non-trivial trade-off between the advantages of structured light profiles and mode broadening, stimulating further investigations in this direction. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Coronary calcifications are an obstacle for successful percutaneous treatment of coronary artery disease patients. The optimal method for delineating calcifications extent is coronary optical coherence tomography (OCT). To identify calcification on OCT and subsequently tailor the appropriate treatment, requires expertise in both image acquisition and interpretation. Image acquisition consists from system calibration, blood clearance by a contrast agent along with synchronization of the pullback process. Accurate interpretation demands careful review by the operator of a segment of 50–75 mm of the coronary vessel at steps of 5–10 frames per mm accounting for 375–540 images in each OCT run, which is time consuming and necessitates some expertise in OCT analysis. In this paper we developed a new deep learning algorithm to assist the physician to identify and quantify coronary calcifications promptly, efficiently and accurately. Our algorithm achieves an accuracy of 0.9903 ± 0.009 over the test set at size of 1500 frames and even managed to find calcifications that were not recognized manually by the physician. For the best knowledge of the authors our algorithm achieves high accuracy which was never achieved in the past.

Diffuse optical tomography (DOT) is a non-invasive imaging technique utilizing multi-scattered light at visible and infrared wavelengths to detect anomalies in tissues. However, the DOT image reconstruction is based on solving the inverse problem, which requires massive calculations and time. In this article, for the first time, to the best of our knowledge, a simple, regression-based cascaded feed-forward deep learning neural network is derived to solve the inverse problem of DOT in compressed breast geometry. The predicted data is subsequently utilized to visualize the breast tissues and their anomalies. The dataset in this study is created using a Monte-Carlo algorithm, which simulates the light propagation in the compressed breast placed inside a parallel plate source-detector geometry (forward process). The simulated DL-DOT system's performance is evaluated using the Pearson correlation coefficient (R) and the Mean squared error (MSE) metrics. Although a comparatively smaller dataset (50 nos.) is used, our simulation results show that the developed feed-forward network algorithm to solve the inverse problem delivers an increment of ∼30% over the analytical solution approach, in terms of R. Furthermore, the proposed network's MSE outperforms that of the analytical solution's MSE by a large margin revealing the robustness of the network and the adaptability of the system for potential applications in medical settings.

In this paper, we present a novel approach, enabling the measurement of nitrate concentrations in natural soil porewater containing natural soil dissolved organic carbon (DOC). The method is based on UV absorbance spectroscopy, combined with fluorescence spectroscopy, for simultaneous analysis of DOC and nitrate concentrations. The analytical procedure involves deduction of the absorption caused by the DOC from the total absorbance in the UV range that is attributed to both DOC and nitrate in the water solution. The analytical concept has been successfully tested in soil water samples obtained from five agricultural sites, as well as in water samples obtained from a commercial hummus soil mixture. We believe that the new analytical concept can provide a scientific foundation for developing a sensor for real-time nitrate concentration measurements in agricultural soils. As such, it can play a significant role in reducing nitrate pollution in water resources, optimizing input application in agriculture, and decreasing food production costs.

A major challenge in use of the optical spectrum for communication and imaging applications is the scattering of light as it passes through diffuse media. Recent studies indicate that light beams with orbital angular momentum (OAM) can penetrate deeper through diffuse media than simple Gaussian beams. To the best knowledge of the authors, in this paper we describe for the first time an experiment examining transmission of OAM beams through biological tissue with thickness of up to a few centimeters, and for OAM modes reaching up to 20. Our results indicate that OAM beams do indeed show a higher transmittance relative to Gaussian beams, and that the greater the OAM, the higher the transmittance also up to 20, Our results extend measured results to highly multi scattering media and indicate that at 2.6 cm tissue thickness for OAM of order 20, we measure nearly 30% more power in comparison to a Gaussian beam. In addition, we develop a mathematical model describing the improved permeability. This work shows that OAM beams can be a valuable contribution to optical wireless communication (OWC) for medical implants, optical biological imaging, as well as recent innovative applications of medical diagnosis.

This manuscript discusses the most relevant aspects of the practical implementation of a long-range Quantum Key Distribution (QKD) link with trusted nodes, achieving the highest possible secret key rate generation within the security and system level constraints. To this purpose, we report on recent pilot studies for the measurements of detection efficiency and source photon statistics for validating the calibration facilities (i) at telecom wavelength for realistic quantum backbone implementation through standard telecommunications grade optical fiber, and (ii) for the telecom and VIS-NIR regime. In addition, since there are circumstances when a fiber optical link may not be available, we will also discuss the characterization of a Free Space Optics (FSO) QKD link. Finally, the manuscript also discusses the problem of information reconciliation in Continuous Variable QKD (CV-QKD) scenarios.

Scattering phenomena affect light propagation through any kind of medium from free space to biological tissues. Finding appropriate strategies to increase the robustness to scattering is the common requirement in developing both communication protocols and imaging systems. Recently, structured light has attracted attention due to its seeming scattering resistance in terms of transmissivity and spatial behavior. Moreover, correlation between optical polarization and orbital angular momentum (OAM), which characterizes the so-called vector vortex beams (VVBs) states, seems to allow for the preservation of the polarization pattern. We extend the analysis by investigating both the spatial features and the polarization structure of vectorial optical vortexes propagating in scattering media with different concentrations. Among the observed features, we find a sudden swift decrease in contrast ratio for Gaussian, OAM, and VVB modes for concentrations of the adopted scattering media exceeding 0.09%. Our analysis provides a more general and complete study on the propagation of structured light in dispersive and scattering media.

Discrete multi-tone (DMT) and optical orthogonal frequency division multiplexing (OFDM) modulations are well-known methods used to transmit high data rate information in visible light communication (VLC) applications over the illumination infrastructure. However, the use of these techniques in a multi-user environment requires effective subcarrier and power allocation design in order to achieve the maximum data rate offered by the spatial distribution of the transmitters and receiver as well as to minimize the efficiency reduction of the illumination system due to the communication. This could be achieved by minimizing the communication signal power in an appropriate way. In this paper, we propose a heuristic allocation algorithm that minimizes the system subcarrier transmitter power while keeping the required data rate and error bit rate. The numerical calculation was done for given parameters. The results indicate that transmitter power reduction of more than 10% in a most scenario is achieved in comparison to previous algorithms.

Millimeter wave (mmWave) communication has raised increasing attentions from both academia and industry due to its exceptional advantages. Compared with existing wireless communication techniques, such as WiFi and 4G, mmWave communications adopt much higher carrier frequencies and thus come with advantages including huge bandwidth, narrow beam, high transmission quality, and strong detection ability. These advantages can well address difficult situations caused by recent popular applications using wireless technologies. For example, mmWave communications can significantly alleviate the skyrocketing traffic demand of wireless communication from video streaming. Meanwhile, mmWave communications have several natural disadvantages, e.g., severe signal attenuation, easily blocked by obstacles, and small coverage, due to its short wavelengths. Hence, the major challenge is how to overcome its shortcomings while fully utilizing its advantages. In this paper, we present a taxonomy based on the layered model and give an extensive review on mmWave communications. Specially, we divide existing efforts into four categories that investigate: physical layer, medium access control (MAC) layer, network layer, and cross layer optimization, respectively. First, we present an overview of some technical details in physical layer. Second, we summarize available literature in MAC layer that pertains to protocols and scheduling schemes. Third, we make an in-depth survey of related research work in network layer, providing brain storming and methodology for enhancing the capacity and coverage of mmWave networks. Fourth, we analyze available research work related to cross layer allocation/optimization for mmWave communications. Fifth, we make a review of mmWave applications to illustrate how mmWave technology can be employed to satisfy other services. At the end of each section described above, we point out the inadequacy of existing work and identify the future work. Sixth, we present some available resources for mmWave communications, including related books about mmWave, commonly used mmWave frequencies, existing protocols based on mmWave, and experimental platforms. Finally, we have a simple summary and point out several promising future research directions.

Data centers are crucial elements in modern information technology. In order to implement the next generation of data centers, new challenges must be overcome. These include reducing the energy consumption, increasing the data rates, reducing the communication latency, increasing the flexibility and scalability, and reducing the maintenance time and cost. One promising way for meeting these challenges is to employ multichannel optical wireless communication as part of the data center hybrid communication network. In this paper, we analyze three technologies that could be used in this context: MIMO (Multiple-in-Multipleout), multiplexing through orbital angular momentum of light, and direct modulation through the large number of modes associated with orbital angular momentum. Our results indicate that these technologies could provide an innovative and flexible means of meeting the challenges of the next generation of data centers.

True-time-delay devices could significantly contribute to improving the performance of many optical systems in applications such as sensing, ranging, communication and signal processing. Delay devices based on spiral optical waveguides are of special interest due to their small size and relatively low power attenuation. In this paper, we propose to fabricate spirals on both sides of a wafer, where the coupling between them is through a vertical interconnect. The novel through-wafer interconnect has a level of attenuation that compares competitively with that obtained with a conventional s-shaped interconnect between two interleaved spirals and considerably simplifies the waveguide design and fabrication.

Free space optical interconnections (FSOIs) are anticipated to become a prevalent technology for short-range high-speed communication. FSOIs use lasers in board-to-board and rack-to-rack communication to achieve improved performance in next generation servers and are expected to help meet the growing demand for massive amounts of inter-card data communication. An array of transmitters and receivers arranged to create an optical bus for inter-card and card-to-backplane communication could be the solution. However, both chip heating and cooling fans produce temperature gradients and hot air flow that results in air turbulence inside the server, which induces signal fading and, hence, influences the communication performance. In addition, the proximity between neighboring transmitters and receivers in the array leads to crosstalk in the received signal, which further contributes to signal degradation. In this Letter, the primary objective is to experimentally examine the off-axis crosstalk between links in the presence of turbulence inside a server chassis. The effects of geometrical and inter-chassis turbulence characteristics are investigated and first-and second-order statistics are derived.

Information Reconciliation (IR) in QKD is a fundamental step in ensuring Alice and Bob share identical set of bits (reconciled key). IR could be done by one-way or two-way channel coding using an auxiliary public authenticated channel to send parities to correct the actual labels so that the sample labels at Alice and Bob match. We assume that communication is performed through an Optical Wireless (OW) or Free Space Optics (FSO) channel, which effects the received signal by a stochastic fading due to jitter in pointing. The effect is that the received samples do not match with the transmitted ones, this is the reason why IR is necessary in such a system. In a previous work, we analyzed the system performance over FSO channel, uncovering the dependence between performance and system parameters such as fading variance or the telescope gain. In this paper we want to study the overall performance and try to obtain optimal values for the parameters that influence the sign error probability.

Lack of real-time information on nutrient availability in cultivated soils inherently leads to excess application of fertilizers in agriculture. As a result, nitrate, which is a soluble, stable and mobile component of fertilizers, leaches below the root zone through the unsaturated zone and eventually pollutes the groundwater and other related water resources. Rising nitrate concentration in aquifers is recognized as a worldwide environmental problem that contributes to water scarcity. Accordingly, developing technologies for continuous in-situ measurement of nitrate concentration in the soils are essential for optimizing fertilizer application and preventing water resource pollution by nitrate. Here we present a conceptual approach for a monitoring system that enables in-situ and continuous measurement of nitrate concentration in soil. The monitoring system is based on absorbance spectroscopy techniques for direct determination of nitrate concentration in soil porewater without pretreatment, such as filtration, dilution, or reagent supplementation. A new analytical procedure was developed to improve measurement accuracy while eliminating the typical measurement interference caused by soil dissolved organic carbon. The analytical procedure was tested at four field sites over 2 years and proved to be an effective tool for nitrate analysis in untreated soil. A soil nitrate-monitoring apparatus, combining specially designed optical flow cells with soil porewater-sampling units, enabled for the first time, real-time continuous measurement of nitrate concentration in the soil. The system provided outstanding and explicit data revealing the complexities of the temporal variations in soil nitrate concentrations in response to irrigation cycles and fertilizer-application pattern. Such real-time measurements of soil nitrate levels are crucial for optimizing fertilizer application to increase agricultural yield while reducing the potential threat of groundwater contamination by down-leaching of nitrate from the soil.

In the last decade data-centers have become a crucial element in our society. As a result, in the coming years there will be increased threat from hackers, who could cause outage of the data-center, extract millions of account details, or steal financial and sensitive information. One way to reduce these threats is to divide the data-center into sub data-centers, and connect them by secure links which prevent access by unauthorized users. A possible technology to connect between the sub data-centers is optical wireless communication (OWC) or free space optics (FSO). An OWC link includes an optical receiver and laser transmitter. The transmitter transmits a light beam that carries information which propagates to the receiver. The light beam carrying the information propagates through the air. In order to increase the security and make the penetration and intrusion difficult quantum key distribution (QKD) is added to the link. By doing so the information exchange between the sub data-centers is encrypted. In this paper we review up to date literature in the field, propose an implementation scheme of an OWC network in sub data-centers, and discuss ways to hack the system.