Accurate and low-latency positioning is a key enabler for optical links with Low Earth Orbit (LEO) satellites, where millisecond-level beam alignment is required to maintain reliable high-data-rate communication. This paper presents a learning-driven dual-line laser scanning framework for fast and precise satellite positioning. Unlike conventional Gaussian-beam acquisition systems that rely on multiple sequential beams or mechanical steering, the proposed approach employs two orthogonal line-shaped laser beams to perform structured optical scanning over the ambiguity region without any moving parts. A physics-based model incorporating atmospheric attenuation, turbulence, and MRR-based reflection is developed, and a data-driven neural estimator is trained to map received optical energy patterns to the satellite's two-dimensional position. Simulation results demonstrate that the learning-driven method achieves near-MAP accuracy with typical errors of 7-10 m and deterministic scanning time of 1-2 ms, while conventional two-stage Gaussian-beam schemes exhibit comparable errors but random sensing durations of up to 5 ms. The proposed framework therefore offers a favorable trade-off between positioning accuracy, computational complexity, and sensing latency, making it a practical candidate for next-generation optical LEO tracking systems.

High-speed vehicular environments require optical systems capable of joint sensing, positioning, and communication (JSPC) without mechanical tracking. Existing optical and integrated sensing-communication approaches often rely on point-source emitters or camera-based receivers, limiting spatial coverage and update rate under highway dynamics. This work introduces a new class of tracking-free optical JSPC systems that combine structured line-laser illumination with modulating retroreflector (MRR) arrays on vehicles. Two orthogonal line lasers perform synchronized longitudinal and transverse scanning to provide continuous, wide-area coverage across the roadway. A coverage-driven analytical framework models the coupling between beam divergence, scan geometry, and dwell-time allocation, enabling joint evaluation of sensing reliability and communication quality. An optimization scheme is developed to adapt scanning and divergence parameters for uniform coverage and power efficiency. Simulation results demonstrate significant improvements in spatial coverage uniformity, link stability, and reliability within a fixed scan period. These results establish a practical pathway toward scalable, turbulence-resilient optical architectures for next-generation vehicular JSPC networks.

Accurate characterization of free-space optical (FSO) channels requires joint estimation of transmitter pointing errors, receiver angle-of-arrival (AoA) fluctuations, and turbulence-induced fading. However, existing literature addresses these impairments in isolation, since their multiplicative coupling in the received signal severely limits conventional estimators and prevents simultaneous recovery. In this paper, we introduce a novel multi-aperture FSO receiver architecture that leverages spatial diversity across a lens array to decouple these intertwined effects. Building on this hardware design, we propose a hierarchical deep learning framework that sequentially estimates AoA, transmitter pointing error, and turbulence coefficients. This decomposition significantly reduces learning complexity and enables robust inference even under strong atmospheric fading. Simulation results demonstrate that the proposed method achieves near-MAP accuracy with orders-of-magnitude lower computational cost, and substantially outperforms end-to-end learning baselines in terms of estimation accuracy and generalization. To the best of our knowledge, this is the first work to demonstrate practical joint estimation of these three key parameters, paving the way for reliable, turbulence-resilient multi-aperture FSO systems.

This paper proposes a hybrid infrastructure-to-vehicle (I2V) communication framework to support future 6G-enabled intelligent transportation systems (ITS) in smart cities. Leveraging existing LED streetlighting infrastructure, the system simultaneously delivers energy-efficient illumination and high-speed wireless connectivity. The proposed scheme integrates visible light communication (VLC) with a complementary terahertz (THz) antenna array to overcome VLC limitations under high ambient light and adverse weather conditions. Key contributions include the design of a VLC/THz access network, seamless integration with lighting infrastructure, a proposed switching-combination (PSC) mechanism, and a physical layout optimization strategy. Using a grid search method, thousands of configurations were evaluated to maximize lighting coverage, received power, signal-to-noise ratio (SNR), signal-to-interference-and-noise ratio (SINR), and minimize outage probability. Results show that optimized lighting coverage improves from 35% to 97%, while hybrid communication coverage increases from 49% to 99.9% at the same power level. Under extreme environmental conditions, the hybrid system maintains up to 99% coverage, compared to 69% with VLC alone. These results demonstrate the scalability, cost-efficiency, and practicality of the proposed system for next-generation ITS deployment.

This paper presents an efficient analytical framework for evaluating the performance of inter-satellite communication systems utilizing orbital angular momentum (OAM) beams under pointing errors. An accurate analytical model is first developed to characterize intermodal crosstalk caused by beam misalignment in OAM-based inter-satellite links. Building upon this model, we derive efficient expressions to analyze and optimize system performance in terms of bit error rate (BER). Unlike traditional Monte Carlo-based methods that are computationally intensive, the proposed approach offers accurate performance predictions. This enables a substantial decrease in computation time while maintaining high accuracy, thanks to the use of analytical expressions for both crosstalk and BER. This fast and accurate evaluation capability is particularly critical for dynamic low Earth orbit (LEO) satellite constellations, where network topology and channel conditions change rapidly, requiring real-time link adaptation. Furthermore, we systematically design and evaluate asymmetric OAM mode sets, which significantly outperform symmetric configurations in the presence of pointing errors. Our results also reveal key insights into the interaction between beam divergence, tracking accuracy, and link distance, demonstrating that the proposed framework enables real-time optimization of system parameters with high fidelity. The analytical findings are rigorously validated against extensive Monte Carlo simulations, confirming their practical applicability for high-mobility optical wireless systems such as LEO satellite networks.

This paper investigates the performance of satellite-based quantum key distribution (QKD) under realistic channel conditions, emphasizing the adverse effects of photon loss introduced by pointing errors and the presence of background photons. By leveraging a stochastic framework, we model the probability distribution of the number of photons detected at the receiver, considering Gaussian beam propagation, finite receiver aperture, and Poisson-distributed background noise. We then evaluate essential QKD performance metrics—such as the quantum key rate, quantum bit error rate (QBER), and outage probability—across a wide range of beam waist sizes and tracking accuracies. Numerical simulations demonstrate how subtle increases in the pointing error variance can drastically reduce the secure key generation rate, particularly for tightly focused beams. These findings highlight the importance of precise pointing systems and careful selection of optical parameters to ensure an acceptable QBER and a sufficiently high secret key rate in inter-satellite QKD links.

Combining free-space optical (FSO) technology with uncrewed aerial vehicles (UAVs) introduces dynamic, rapidly deployable relay systems, overcoming line-of-sight (LoS) constraints and extending high-speed communication networks’ reach, albeit with critical considerations of weight and power consumption. There are two main types of optical communication technologies for relays: conventional optical relays, such as amplify-and-forward (AF)/decode-and-forward (DF) systems, and intelligent reflecting surface (IRS)-based relays, each facing significant challenges. To this end, this paper introduces a novel hybrid two-way free-space optical (FSO) relay system utilizing modulating retro-reflector (MRR) technology to address specific challenges in UAV-based optical communication. Unlike traditional amplify-and-forward (AF) and decode-and-forward (DF) relay systems, which struggle with power consumption and IRS-based systems that suffer from sensitivity to angular fluctuations, the proposed MRR-based approach offers a strategic compromise. The proposed system combines MRR technology with conventional lens-based systems and network coding to enhance stability against UAV’s angular movements. Performance evaluations reveal that while the proposed MRR-based relay system offers significant advantages under conditions of high angular instability, it achieves comparable or superior performance relative to AF/DF and IRS-based systems within certain operational parameter ranges. This study thus advances the discussion on UAV-based relay solutions by offering an in-depth analysis of the proposed system’s application potential and its specific constraints.

This paper focuses on the optimal design of a modulated retroreflector (MRR) laser link to establish a high-speed downlink for cube satellites (CubeSats), taking into account the weight and power limitations commonly encountered by these tiny satellites. To this end, first, a comprehensive channel modeling is conducted considering key real channel parameters including mechanical gimbal error, fast steering mirror angle error, laser beamwidth, MRR area, atmospheric turbulence, and channel coherence time. Accordingly, a closed-form expression for the distribution of the received signal is derived and utilized to propose a maximum likelihood based method to sense and estimate the initial position of the satellite. Subsequently, the distribution of the distance estimation error during the sensing phase is formulated as a function of the laser beamwidth and the gimbal error, which enables us to fine-tune the optimal laser beamwidth to minimize sensing time. Moreover, using the sensing and initial satellite distance estimation, two positioning algorithms are proposed. To compare the performance of the proposed positioning method, we obtain the lower bound of the positioning error as a benchmark. Finally, by providing comprehensive simulations, we evaluate the effect of different parameters on the performance of the considered MRR-based system in both the sensing and positioning phases.

Given the growing significance of CubeSats for real-time Earth monitoring and space networking, there is an increasing demand for high-speed links for CubeSats facing constraints related to the weight, dimensions, and power consumption of telecommunication equipment. This article addresses such a need by designing a modulating retroreflector (MRR)-based optical downlink system tailored for fast-moving CubeSats, highlighting joint tracking and communication operations using a single transmitter for high data rates. Key contributions encompass precise system characterization, the design of a dual-transmitter system to maximize channel capacity, derivation of channel capacity as a function of 2M + 4 random variables, and the development of an MRR-based CubeSat downlink system. Subsequently, leveraging the obtained analysis and results, we design a system with a single transmitter, enabling simultaneous tracking and communication operations through optimal adjustments of beam timing and placement in the satellite’s vicinity. Pertinent analyses demonstrate optimal laser beam adjustments to achieve maximum capacity while maintaining tracking accuracy. Monte Carlo simulations are used to validate a closed-form expression for efficient optimization of system parameters. Comprehensive simulations assess the effect of different parameters, offering crucial insights for optimal system design.

Low Earth orbit (LEO) satellite constellations are emerging as a key enabler of next-generation communications, offering global coverage and significantly lower latency compared to traditional terrestrial networks and geostationary satellites. However, further latency reduction is essential for time-critical applications such as real-time sensing, autonomous systems, and interactive services. One critical bottleneck is the optical-to-electrical (O/E) and electrical-to-optical (E/O) conversions at intermediate nodes in multi-hop links, which introduce unwanted processing delays. To address this, we investigate an all-optical relay system based on Optical Hard Limiters (OHL), which operate purely in the optical domain to suppress noise and restore signal quality without requiring O/E conversions. First, we present a rigorous analysis of inter-satellite multi-relay communication under the OHL relaying architecture, comparing it against conventional Amplify-and-Forward (AF) and Decode-and-Forward (DF) schemes. Through this comparison, we highlight both the advantages and limitations of OHL relays, including their particular sensitivity to parameter choices such as the threshold setting and divergence angle at the transmitter. Recognizing that a LEO constellation is inherently time-varying—satellites move relative to one another, causing continuous changes in link distances and tracking errors—we propose a joint optimization strategy. This scheme adaptively tunes the OHL decision threshold and beam divergence in real time to maintain optimal performance, ultimately lowering error rates and latency. Extensive simulations in a large-scale LEO network demonstrate the viability of our method and offer insights into practical implementation for next-generation inter-satellite communication systems.

Terahertz (THz) band is widely nominated to be exploited in next wireless networks to meet the high demand on data rates. However, unlike lower frequency bands, several challenges come up while designing a transmission system over the THz band. Among these challenges is the hardware impairments at the transmitter front-end. It is well known that hardware impairments limit the error performance of any transmission system, where a lower bound on the error rate is usually noticed. Such an impact becomes more severe as the operating frequency increases, which significantly degrades the transmission over THz band. To this end, this paper proposes an adaptive modulation scheme that is able to overcome this problem. Moreover, the optimal detector for the proposed adaptive modulation scheme is presented. Mathematical modeling and analysis of the performance of the conventional QAM and the proposed modulation scheme are included along with simulation results that verify the analytical findings. Results indicate that the error performance of the proposed scheme is much better than conventional QAM where no error floor is noticed.

Involving Unmanned Aerial Vehicles (UAVs) in wire-less networks has been widely investigated in the literature considering different scenarios such as emergency scenarios in which UAV(s) can play a significant role by compensating the damaged/lost network's components. For example, Sensor Networks (SNs) in emergency scenarios may lose some sensor nodes or the Central Entity (CE) itself, which requires fast, prompt and efficient alternative to replace them. Therefore, UAVs are widely nominated to such a role due to their flexibility and maneuverability. However, compared to ground-based entities, UAVs suffer from the continuous position fluctuations, which directly affects the antenna's orientation. Such an effect becomes a serious challenge in high frequency links such as millimeter wave (mmWave) links which are very sensitive to antennas misalignment. In this paper, the performance of UAV-based SNs is addressed by analyzing the impact of UAV's vibration on the performance metrics including detection and false-alarm probabilities. To this end, two network models are adopted, namely, Ground-based Hybrid SN (G-HSN) and Aerial-based Hybrid SN (A-HSN), depending on whether the CE is ground or aerial node. A mathematical framework is followed to express performance metrics in closed form expressions considering practical conditions including channel fading, orientation fluctuations of directional mmWave antennas and path loss. Simulation results validate the accuracy of the derived mathematical expressions and depict the impact of different operational parameters.

This paper presents a novel approach for joint Terahertz (THz) communication and three-dimensional (3D) map reconstruction using an Unmanned Aerial Vehicle (UAV). Due to the need for precise mapping to provide Line-of-Sight (LoS) THz communication services, our approach leverages the UAV's trajectory to initiate the reconstruction and updating of the 3D environment in real-time. The UAV starts without any prior knowledge of the target area, establishing THz communications with users scattered among 3D obstacles. A comprehensive system model is developed, incorporating realistic antenna patterns, UAV oscillations, and received signal power modeling for accurate analysis. We establish an adaptive methodology for 3D environment modeling, dynamically constructing and refining a grid-based obstacle map. A dynamic algorithm for real-time 3D map reconstruction is implemented, utilizing received signal strengths to update the environmental model. Detailed simulations validate the effectiveness of our proposed methods, demonstrating significant improvements in computational efficiency and real-time decision-making in UAV-assisted communication networks. Our results highlight the potential of this joint approach in enhancing operational efficiency and communication reliability under varying environmental conditions.

Exploiting the high-frequency bands, such as millimeter wave band (mmWave), has become a pressing need due to the increasing demand on the high data rates. However, two main challenges are still hindering the usage of mmWave band, which are represented by the short transmission distance and strict Line-of-Sight (LoS) requirements. To this end, relaying schemes have been widely nominated to address these two challenges, where the transmission distance can be extended and the LoS can be attained by the aid of a well-positioned relay. One of the promising spectral-efficient relaying schemes is the well known Two-Way Relaying (TWR). In this paper, the performance of the TWR scheme is investigated for aerial links operating over the mmWave band. Specifically, the bit error rate (BER) is analyzed for a dual-hop system in which source, relay and destination are represented by hovering unmanned aerial vehicles. A closed form expression of the average BER is derived considering the impact of the antennas' fluctuations, modulation order, transmission distance, beamwidth, path loss and channel fading. Simulation results are explored to investigate the impact of all operational parameters.

The main subject of this work is to make a detailed comparison between the performance of free-space optical (FSO) and terahertz (THz) links under different conditions. To this end, we first perform a detailed modeling of the FSO and THz channels, taking into account all real channel parameters. Then we compare the performance of THz and FSO links using two important wireless communication performance metrics, i.e., channel capacity and outage probability. We mathematically show that, unlike FSO links, the pointing errors of THz links are not function of linklength. Finally, by examining the strengths and weaknesses of both technologies, we show that increasing the linklength has a more destructive effect on FSO links compared to the THz links. For shorter linklength, FSO links have better performance, however, with the increase in linklength, THz has the ability to reach higher capacity than FSO links.

As an alternative solution for quick disaster recovery of backhaul/fronthaul links, in this paper, a dynamic unmanned aerial vehicles (UAV)-assisted heterogeneous (HetNet) network equipped with directional terahertz (THz) antennas is studied to solve the problem of transferring traffic of distributed small cells. To this end, we first characterize a detailed three-dimensional modeling of the dynamic UAV-assisted HetNet, and then, we formulate the problem for UAV trajectory to minimize the maximum outage probability of directional THz links. Then, using deep reinforcement learning (DRL) method, we propose an efficient algorithm to learn the optimal trajectory. Finally, using simulations, we investigate the performance of the proposed DRL-based trajectory method.

We propose a fixed-wing unmanned aerial vehicles (UAV)-based millimeter wave (mmWave) backhaul architecture that is offered as a cost effective and easy to deploy solution, to connect a disaster or remote area to the nearest core network. First, we fully characterize the single relay fixed-wing UAV-based communication system by taking into account the effects of realistic physical parameters, such as the UAV’s circular path, critical points of the flight path, heights and positions of obstacles, flight altitude, tracking error, the severity of UAV’s vibrations, the real 3D antenna pattern, mmWave atmospheric channel loss, temperature and air pressure. Second, we derive the distribution of the signal-to-noise ratio (SNR) metric, which is based on the sum of a series of Dirac delta functions. Using the SNR distribution, we derive analytical expressions for the outage probability and the ergodic capacity of the considered system as a function of all system parameters. To provide an acceptable quality of service for longer link lengths, we extend the analytical expressions to a multi-relay system. The accuracy of the analytical expressions are verified by Monte-Carlo simulations. Finally, by providing sufficient simulation results, we investigate the effects of key channel parameters such as antenna pattern gain and flight path on the performance of the considered system; and we carefully analyze the relationships between those parameters in order to maximize the average channel capacity.

The main contribution of this paper is to analyze a long networked flying platform (NFP)-based millimeter wave (mmWave) backhaul link that is offered as a cost effective and easy to deploy solution to connect a disaster or remote area to the nearest core network. The same network model can be considered for interlinking Low Earth Orbit (LEO) satellite constellations with different geometry and channel characteristics. For this aim, we characterize the backhaul channel as a function of realistic physical parameters such as heights and distances of obstacles along the route, flight altitude and the intensity of NFPs' vibrations, the actual 3D antenna pattern, etc. For the characterized channel, we derive an analytical closed-form expression for the outage probability. Finally, using the obtained results, we provide a fast algorithm for the optimal parameter design of the considered system that minimizes the cost.

Weight reduction and low power consumption are key requirements in the next generation of unmanned aerial vehicle (UAV) networks. Employing modulating retro-reflector (MRR)-based free space optical (FSO) technology is an innovative technique for UAV-to-ground communication in order to reduce the payload weight and power consumption of UAVs which leads to increased maneuverability and flight time of UAV. In this paper, we consider an MRR-based FSO system for UAV-to-ground communication. We will show that the performance of the considered system is very sensitive to tracking errors. Therefore, to assess the benefits of MRR-based UAV deployment for FSO communications, the MRR-based UAV FSO channel is characterized by taking into account tracking system errors along with UAV’s orientation fluctuations, link length, UAV’s height, optical beam divergence angle, effective area of MRR, atmospheric turbulence and optical channel loss in the double-pass channels. To enable effective performance analysis, tractable and closed-form expressions are derived for probability density function of end-to-end signal to noise ratio, outage probability and bit error rate of the considered system under both weak-to-moderate and moderate-to-strong atmospheric turbulence conditions. The accuracy of the analytical expressions is verified by extensive simulations. Analytical results are then used to study the relationship between the optimal system design and tracking system errors.

In this article, the performance of UAV-based mmW links is investigated when UAVs are equipped with square array antennas. The 3GPP antenna propagation patterns are used to model the square array antenna. It is shown that the square array antenna is sensitive to both horizontal and vertical angular vibrations of UAVs. In order to explore the relationship between the vibrations of UAVs and their antenna pattern, the UAV-based mmW channels are characterized by considering the large scale path loss, small scale fading along with antenna patterns as well as the random effect of UAVs' angular vibrations. To enable effective performance analysis, tractable and closed-form statistical channel models are derived for aerial-to-aerial (A2A), ground-to-aerial (G2A), and aerial-to-ground (A2G) channels. The accuracy of analytical models is verified by employing Monte Carlo simulations. Analytical results are then used to study the effect of antenna pattern gain under different conditions for the UAVs' angular vibrations for establishing reliable UAV-assisted mmW links in terms of achieving minimum outage probability. Simulation results show that the performance of UAV-based mmW links with directional antennas is largely dependent on the random fluctuations of hovering UAVs. Moreover, UAVs with higher antenna directivity gains achieve better performance at larger link length. However, for UAVs with lower stability, lower antenna directivity gains result in a more reliable communication link. Finally, based on the geometrical properties of a given region, we investigate the optimal antenna pattern along with the optimal aerial position for UAV relay to attain minimum outage probability.

The integration of unmanned aerial vehicles (UAVs) and millimeter wave (mmWave) wireless systems has been recently proposed to provide high data rate aerial links for next generation wireless networks. However, establishing UAV-based mmWave links is quite challenging due to the random fluctuations of hovering UAVs which can induce antenna gain mismatch between transmitter and receiver. To assess the benefit of UAV-based mmWave links, in this paper, tractable, closed-form statistical channel models are derived for three UAV communication scenarios: (i) a direct UAV-to-UAV link, (ii) an aerial relay link in which source, relay, and destination are hovering UAVs, and (iii) a relay link in which a hovering UAV connects a ground source to a ground destination. The accuracy of the derived analytical expressions is corroborated by performing Monte-Carlo simulations. Numerical results are then used to study the effect of antenna directivity gain under different channel conditions for establishing reliable UAV-based mmWave links in terms of achieving minimum outage probability. It is shown that the performance of such links is largely dependent on the random fluctuations of hovering UAVs. Moreover, higher antenna directivity gains achieve better performance at low SNR regime. Nevertheless, at the high SNR regime, lower antenna directivity gains result in a more reliable communication link. The developed results can therefore be applied as a benchmark for finding the optimal antenna directivity gain of UAVs under the different levels of instability without resorting to time-consuming simulations.

We consider the use of free-space optical communication for fast moving platforms such as high-speed trains, where the sampling clock offset is randomly changing, in addition, the receiver does not have any information on the instantaneous channel fading coefficient. By employing multiple samplers at the receiver, we propose a class of sequence detection methods for the case of On-Off keying (OOK) signaling without using any training sequence. First, we study maximum likelihood-based detection, which has a relatively high-computational complexity. Second, by employing generalized likelihood ratio test, we propose a more practical blind sequence detection method of reduced complexity. To further reduce the computational complexity, third, we propose a novel scheme that uses two wavelengths at the transmitter and differential blind detection at the receiver. Fourth, to benefit from diversity gain with this differential scheme, we consider the use of sufficiently different wavelengths along with sufficient spatial separation between the transmitters and/or the receivers, where we propose an efficient blind detection method. The pros and cons of the proposed detection methods are contrasted through numerical results and their processing loads are compared.

Recently, the use of multi-rotor (MR) unmanned aerial vehicles (UAVs) has emerged as a promising solution for establishing flexible free-space optical communication links. We address, in this paper, the accurate channel modeling to assess the benefits of MR UAV-based deployment for such links. In particular, in the absence of active tracking subsystems, we derive statistical models for ground-to-UAV, UAV-to-UAV, and UAV-to-ground links over both Gamma-Gamma and log-normal atmospheric turbulence models. Unlike previous works on this topic, our proposed model considers the joint effect of atmospheric turbulence along with position and angle-of-arrival fluctuations. The high accuracy of the proposed analytical models is verified by comparing numerically solved and Monte Carlo simulation results in terms of link outage probability. We further discuss the impact of different transmitter/receiver parameters and their optimization in view of maximizing the link availability.