This letter addresses the growing demand for ultra-reliable low-latency communications (URLLC) in free-space optics (FSO)-based UAV systems. Notably, we propose an FSO-based UAV framework that employs cross-packet hybrid automatic repeat request (XP-HARQ) combined with adaptive rate/power control. In this design, the UAV's long-term transmit power is minimized by jointly adjusting the transmission rate and power across XP-HARQ transmissions. To solve the optimization problem under stringent URLLC constraints, we leverage deep reinforcement learning (DRL). The performance metrics, including average transmit power, achievable throughput, and energy efficiency, are analytically characterized over time-varying UAV-to-UAV channels. Simulation results corroborate the superiority of the proposed system using XP-HARQ over conventional ARQ/HARQ schemes in FSO systems and quantify the transmit power required under different URLLC demands. Finally, we investigate the impact of imperfect channel state information (CSI) on system performance, highlighting practical design considerations.

This letter addresses the transmit power minimization challenge in unmanned aerial vehicle (UAV)-assisted hybrid free-space optical hybrid automatic repeat request (IR-HARQ), a cornerstone for 6G's ultrareliable low-latency communications (URLLC). We propose a deep reinforcement learning (DRL)-driven framework, leveraging proximal policy optimization (PPO), to adapt power allocation across retransmissions via an agent-learned policy dynamically. This ensures reliable packet delivery under stringent delay bounds while accounting for channel impairments, including atmospheric attenuation, scintillation fading, and beam pointing errors. The system model incorporates SNR-based FSO/THz switching, with FSO as the primary link and THz as backup, evaluated through outage probabilities tailored to IR-HARQ, chase combining HARQ (CC-HARQ), and automatic repeat request (ARQ). Simulations across diverse environmental conditions reveal the proposed DRL-IR-HARQ hybrid achieves up to 0.7 dBm savings over THz-only baselines and conventional HARQ protocols, underscoring its robustness for energy-efficient 6G aerial backhauls and disaster-resilient networks.

Non-terrestrial networks (NTNs), incorporating uncrewed aerial vehicles (UAVs) and optical base stations (OBSs), are emerging as a key architectural component for the Sixth Generation (6G) wireless networks, particularly in supporting a wide range of vehicular services in the Internet of Vehicles (IoV). In parallel, free-space optical (FSO) and sub-terahertz (sub-THz) communications are expected to play a central role in 6G due to their abundant spectrum resources. However, the deployment of UAV-assisted vehicular services faces significant challenges, as highly dynamic vehicle mobility and time-varying atmospheric turbulence introduce severe link fluctuations and reliability issues. A hybrid FSO/sub-THz communication link is a potential solution to this problem by enhancing link reliability and service continuity, but it necessitates an intelligent and adaptive switching mechanism. To address this, we propose a deep reinforcement learning (DRL) algorithm that integrates both hard-switching and soft-switching mechanisms to guarantee the UAV-supported quality-of-service (QoS) through real-time trajectory and link optimization. The hybrid FSO/sub-THz link is modeled by considering atmospheric attenuation, fading, pointing errors, blockage by buildings, and weather conditions. Simulation results indicate that the trained UAV can effectively learn from the dynamic environment and maintain robust performance using the proposed DRL-based approach.

In this paper, we investigate a mixed free-space optics (FSO)-radio frequency (RF) downlink communication system enhanced by a simultaneous lightwave information and power transfer (SLIPT)-enabled uncrewed aerial vehicle base station (UAV-BS) and a high-altitude platform (HAP)-mounted optical reconfigurable intelligent surface (ORIS). We develop overall optimization frameworks for end-to-end systems aimed at minimizing transmitted power at optical ground station (OGS) for backhaul link or maximizing the multiuser fairness rate in the access link. This is achieved by jointly optimizing the UAV-BS placement, beamforming strategy, OGS power allocation, and power-splitting (PS) ratio under energy efficiency and quality of service (QoS) constraints. The formulated optimization problems are highly non-linear and non-convex, posing significant challenges for conventional methods. To address this, we employ inner approximation techniques and propose an iterative algorithm to achieve efficient solutions. Simulation results demonstrate substantial performance gains compared to conventional benchmarks, highlighting the efficacy of the proposed approach.

This paper analyzes the physical layer security (PLS) of a mixed free-space optics (FSO)–radio frequency (RF) non-terrestrial network (NTN) employing artificial noise (AN). Unlike conventional RF-based PLS, we show that AN in mixed FSO–RF NTNs exhibits a cross-link coupling effect, where FSO pointing errors, geometric loss, and error propagation significantly influence the effectiveness of AN injected only on the RF hop. Closed-form expressions for bit error rate (BER), secrecy capacity, and secrecy outage probability (SOP) are derived under realistic NTN conditions. Numerical results reveal several key findings. First, without AN, the secrecy capacity remains zero regardless of transmit power, while AN creates a clear activation threshold enabling positive secrecy. Second, the optimal AN power-allocation factor is non-monotonic and depends on transmit power. Third, increasing the number of high altitude platform (HAP) antennas substantially reduces SOP by more than an order of magnitude. Finally, rain attenuation creates critical degradation regions where secure transmission is possible only under high AN power. These results demonstrate that AN plays an essential and uniquely different role in securing multilayer NTN architectures.

Underwater optical wireless communication (UOWC) has difficulties in fulfilling ultra-reliable low-latency communication (URLLC) standards owing to channel distortions, including absorption, scattering, and oceanic turbulence. This paper presents a deep reinforcement learning (DRL) approach utilizing proximal policy optimization (PPO) to concurrently adjust transmit power and coding rate in a point-to-point UOWC system employing hybrid automatic repeat request (HARQ) protocols chase combining (CC-HARQ) and incremental redundancy (IR-HARQ) capitalizing on statistical channel information and signal-to-noise ratio feedback, structured as a Markov decision process (MDP) with rewards that penalize power consumption and delay infractions. By reducing the long-term average power while adhering to stringent delay constraints (e.g., 99.9% dependability at 13 dBm in pristine marine conditions), the approach enables energy-efficient and dependable UOWC for Beyond 5G (B5G) and 6G applications, such as ocean monitoring.

This paper addresses the problem of ensuring high-capacity, reliable wireless connectivity in temporary or disaster-stricken urban environments. We propose an optical intelligent reflecting surface (OIRS)-enhanced free-space optical (FSO) backhaul framework integrated with unmanned aerial vehicles (UAVs) to overcome the limitations of conventional FSO systems, such as line-of-sight (LOS) blockages. Specifically, OIRS deployed on high-rise buildings intelligently redirects optical beams, creating virtual LOS paths and stabilizing FSO links between the ground station and UAVs. To fully exploit this architecture, we develop a comprehensive channel model that accounts for path loss, turbulence-induced fading, and pointing errors, and introduce the OPT-UAV algorithm for joint UAVs 3D placement, user association, and bandwidth allocation under backhaul capacity constraints. Numerical results demonstrate that the proposed framework improves fairness and coverage by serving up to 67% of mobile users, compared to 62% with baseline methods, such as the TLA algorithm, while maintaining competitive throughput. These results confirm the potential of OIRS-assisted mixed FSO/RF systems as a scalable and resilient solution for smart city deployments, disaster recovery, and temporary high-traffic events.

This paper investigates the integration of active reconfigurable intelligent surfaces (ARISs) with uncrewed aerial vehicles (UAVs) in a mixed free-space optics radio frequency (FSO-RF) downlink communication system, enabling simultaneous lightwave information and power transfer (SLIPT). The proposed architecture addresses key challenges in UAV-based networks, including limited endurance and backhaul constraints, by allowing the UAV to harvest energy from the optical backhaul while transmitting RF signals enhanced via ARIS to ground users. The system design aims to maximize the minimum achievable rate among users by jointly optimizing the UAV's beamforming strategy, 3D placement, ARIS reflection coefficients, optical ground station (OGS) transmit power and the power splitting (PS) ratio at the UAV. An alternating optimization framework is developed to decompose the resulting non-convex problem into efficiently solvable subproblems using inner approximation techniques. Simulation results confirm that the proposed approach significantly outperforms baseline schemes, such as passive RIS, fixed UAV deployment, and static PS configurations, delivering improved rate fairness and energy efficiency. These results demonstrate the potential of ARIS-assisted SLIPT-enabled UAVs to support robust and sustainable downlink communications in next-generation wireless networks.

Future 6G networks envision nonterrestrial networks (NTNs) featuring various airborne devices, such as unmanned aerial vehicles (UAVs), to enable flexibility, rapid deployment, and ubiquitous coverage. Free-space optics (FSO), a promising communication technology, aims to connect network devices across the Earth, sky, and space. This article focuses on the innovative concept of simultaneously transmitting data and energy to an operational UAV from a core network, with the assistance of reconfigurable intelligent surfaces (RIS) to navigate through cloudy regions. The FSO link employs the simultaneous lightwave information and power transfer (SLIPT) technique, incorporating a power-splitting strategy that allocates received power for data decoding and wireless energy charging. To enhance data transmission, we introduce an adaptive rate design with QoS awareness. The analyses in this study assess four key performance metrics: 1) data transmission, quantified by the transmission rate; 2) energy transmission, evaluated based on harvested power; 3) UAV lifespan, represented by the remaining operational time for different SLIPT-powered UAV types; and 4) energy efficiency, defined as the ratio of data transmitted to total energy expended and harvested. The proposed system, which integrates SLIPT, RIS, and adaptive rate design, demonstrates significant improvements in the lifespan and energy efficiency of the UAV, validating its effectiveness under challenging operational conditions. Finally, the theoretical results are verified with the Monte Carlo simulation.

This paper investigates hybrid free-space optics (FSO)/radio frequency aerial access networks (AANs) using a high-altitude platform (HAP) and multiple UAVs to dynamically serve terrestrial users under varying environmental conditions, such as atmospheric turbulence and cloud-induced attenuation. The optical intelligent reflecting surfaces (OIRS), mounted on the HAP, enhance the FSO signal distribution to multiple UAVs by enabling precise beam manipulation, improving link reliability, and increasing network scalability. A deep reinforcement learning (DRL)-based approach is developed to optimize UAV placement and user association in real time, maximizing end-to-end throughput while adhering to backhaul capacity constraints. The study takes into account FSO channel impairments, including path loss, turbulence-induced fading, and pointing misalignment, modeled using log-normal distributions. Numerical results demonstrate that the dynamic deployment of multi-UAV configuration, trained under realistic cloudy conditions, significantly outperforms single-UAV and static deployment strategies, achieving higher data rates and stable user connectivity. This work highlights the potential of deploying OIRS-assisted AANs supporting multiple UAVs to realize robust and high-performance 6G networks.

This paper proposes an optimal spatial resource allocation strategy for optical intelligent reflecting surface (OIRS)assisted non-terrestrial networks (NTN) utilizing free-space optical (FSO) communication to support multiple unmanned aerial vehicles (UAVs). The study investigates the deployment of OIRS on a high-altitude platform (HAP) to enhance the system’s coverage and capacity under challenging atmospheric conditions, including cloud attenuation, turbulence-induced fading, and beam spreading loss. A novel algorithm is developed to maximize the number of operational UAVs and the sum rate by efficiently allocating OIRS elements based on the received signal-to-noise ratio (SNR). The proposed approach is compared with conventional methods, such as round-robin and exhaustive search, demonstrating superior performance with reduced computational complexity. The numerical results validate the effectiveness of our strategy, achieving near-optimal performance while maintaining scalability for large-scale NTN, making it a promising solution for future 6G communication systems.

Free-space optical (FSO) communication, with its massive bandwidth, has established a reputation for delivering extremely high-speed connections. The use of an intelligent reflecting surface (IRS) in FSO systems is an innovative approach to overcoming the inherent limitations of line-of-sight connectivity. This paper addresses the optical IRS (OIRS)-assisted FSO systems to provide high-speed internet of vehicles (IoV). Notably, the space division multiple access (SDMA) protocol is employed by a single OIRS to support multiple users. Performance metrics, including system outage and average bit error rate (BER), are analytically analyzed, taking into account the combined effects of interference from OIRS regions, pointing errors, and atmospheric turbulence. Numerical results exploit the proper OIRS region to maximize the performance of OIRS-based SDMA FSO systems.

To cope with the scarcity of radio frequency (RF) counterparts, free-space optics (FSO) based on satellite communications technologies have recently gained a lot of interest. Firstly, this investigates the security of space-to-ground intensity modulation/direct detection FSO satellite communications in various effects from the physical world, such as propagation loss, beam misalignment, cloud attenuation, and fading caused by atmospheric turbulence. Next, A wiretap channel composed of a genuine broadcaster Alice (i.e., the satellite), a legitimate user Bob, and an eavesdropper Eve is considered over turbulent channels characterized by the Fisher-Snedecor $\mathcal{F}$ distribution. In addition, the closed-form expressions of the secrecy performance metrics, including average secrecy capacity, secrecy outage probability, and strictly positive secrecy capacity, are derived in our study. Finally, the numerical findings indicate that the satellite altitude of 600 km should be used to achieve a secrecy outage of roughly 50% for the whole turbulence regime. In addition, high levels of cloud liquid water content (CLWC) could improve the secrecy performance as it is shown that, the average secrecy capacity increases by about 12% when the CLWC increases from $1\mathrm{~mg}/\mathrm{m}^{3}$ to $2\mathrm{~mg}/\mathrm{m}^{3}$.

Underwater wireless optical communications are a developing alternative to meet the increasing need for high-speed connections in oceans and seas. Optical wireless communications (OWCs) are more secure and less susceptible to eavesdropping compared to acoustic communications or radio frequency (RF) communications due to their narrow optical beam coverage and reliance on line-of-sight components. Nevertheless, the existence of a hostile eavesdropper can compromise the level of confidentiality achieved by OWC networks. This article provides a concise overview of the latest research conducted on physical layer security (PLS) in underwater optical wireless communication (UOWC). Furthermore, this work presents the relevant unresolved matters, approaches for enhancing secrecy performance, and potential areas for further research.

Air-ground integrated network (AGIN) incorporating high-altitude platforms (HAP), unmanned aerial vehicles (UAV), and ground base stations (BS) has been recently rec-ognized as a promising architecture for 6G wireless networks. In addition, free-space optical (FSO) technology has shown its potential for delivering exceptionally high-speed data connections over a long distance. While previous works on FSO-based AGIN mainly focused on point-to-point connectivity, this study instead addresses the context of multiple users. This, in turn, raises concerns about the effective multiple access control (MAC) protocol design. In this study, we analyze the performance of MAC protocols, which jointly employ the rate adaptation and bandwidth allocation, in FSO-based AGIN. Particularly, we exploit the performance of different rate adaptation/bandwidth allocation-based MAC protocols for UAV-aided relaying between multiple BSs and HAP via FSO links. Performance metrics are analytically obtained based on Markov models, including frame loss probability, system throughput and average delay. Numerical results offer insights for properly choosing MAC protocols for FSO-based AGIN towards 6G wireless networks.

In response to the dearth of radio frequency (RF) equivalents, there has been a recent surge in interest in optical wireless communication in underwater environments. To ensure a strong line-of-sight (LOS) connection, the intelligent reflecting surface (IRS) is installed to create a virtual LOS. Then, the first part of this study looks into the security of underwater optical wireless communication (UOWC) in relation to a number of real-world phenomena, including oceanic propagation loss, oceanic turbulence, and IRS-induced geometric loss. Then, a wiretap channel with three authorized users - a reputable broadcaster named Alice (the submarine), a law-abiding user named Bob, and an eavesdropper named Eve - is examined over turbulent channels that exhibit the Log-normal distribution. Furthermore, our study derives the closed-form formulas for the secrecy performance measures, secrecy outage probability, and secrecy throughput. Finally, the numerical results show how the impact of oceanic turbulence-induced fading and distance between Bob’s and Eve’s positions on the secrecy system performance.

Free-space optics (FSO)-based non-terrestrial networks (NTN) have garnered significant attention as a potential technology for forthcoming 6G wireless communications due to their exceptional data rate and extensive global coverage capability. Nevertheless, atmospheric attenuation, cloud attenuation, geometric loss, and atmospheric turbulence present numerous difficulties in developing these networks. To cope with these difficulties, we propose to apply a joint adaptive modulation and power control (JAMPC) scheme to FSO-based NTN. Our proposed JAMPC algorithm aims to enhance energy efficiency while guaranteeing the targeted outage probability, bit-error rate, and the required data rate. We develop mathematical models and derive closed-form expressions to implement the proposed algorithm and solve the optimization problem. The numerical results confirm that the JAMPC scheme helps NTN provide better energy efficiency and the ability to adapt to various channel conditions.

Underwater wireless communication is rapidly advancing, finding applications in diverse fields such as oceanography, defense, and commercial ventures. However, ensuring security in such transmissions is crucial due to the sensitive nature of the data involved and the challenges posed by the underwater environment. While classical encryption techniques provide some level of security, the emergence of quantum computing presents opportunities and challenges. Quantum key distribution (QKD) offers theoretically unbreakable encryption, making it an attractive solution. Extending QKD capabilities to underwater environments is a significant endeavor in this context. This paper explores the feasibility of applying an entanglement-based non-coherent QKD protocol inspired by the BBM92 protocol to underwater visible light communication (VLC)/QKD systems. We investigate the system's design criteria and analyze its secret key performance, addressing challenges such as water absorption and turbulence-induced fading, focusing on addressing unauthorized receiver attacks. Through analysis and the considered case study, the feasibility and efficacy of this approach are explored, contributing to the advancement of secure underwater communications. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement