Reliable communication infrastructure is a fundamental component of Intelligent Transport Systems (ITSs), particularly in scenarios involving maritime corridors and emergency traffic management. In locations where optical fiber deployment is geographically constrained, unmanned aerial vehicle (UAV)-assisted free-space optical (FSO) relay links provide a flexible and rapidly deployable alternative. However, atmospheric attenuation, turbulence-induced fading, and wind-induced UAV misalignment can severely degrade link reliability and disrupt real-time transport data streams. This study proposes a payload-efficient multiple-input multiple-output free-space optical (MIMO-FSO) relay architecture based on a multi-output/single-input (MOSI) uplink and a single-output/multi-input (SOMI) downlink. Here, MOSI denotes multiple ground-based transmit apertures directed toward a single UAV receiving aperture, whereas SOMI denotes one UAV transmitting aperture serving multiple ground-based receiving apertures. Unlike conventional symmetric UAV-assisted MIMO-FSO relays that may duplicate diversity hardware on the aerial node, the proposed design shifts the parallel optical branches to the ground stations and keeps only one optical receiver and one optical transmitter on board the UAV. Under the adopted 4 × 4 comparison assumption, this reduces the UAV-side optical branch count from eight to two, corresponding to a 75% branch-count reduction proxy. System performance is evaluated over a 1.54 km relay link. The analytical framework describes Beer–Lambert attenuation, log-normal/gamma–gamma turbulence, and statistical pointing errors; in the OptiSystem implementation, their combined effects are represented by equivalent aggregate losses of 25 dB/km for atmospheric absorption/scattering and 25.5 dB/km for turbulence- and pointing-related degradation. Comparative simulations for SISO, 2 × 2, and 4 × 4 configurations show that the proposed 4 × 4 architecture increases the Q-factor from 8.38 to 18.25 and changes the OptiSystem-reported minimum BER from 2.73 × 10−17 to 9.95 × 10−75. Because a finite simulation cannot statistically validate error probabilities of this magnitude through raw error counting, values far below 10−12 are interpreted primarily as comparative indicators of receiver decision margin. The findings provide simulation-based evidence that the proposed architecture is a scalable candidate for resilient optical wireless backhaul in smart transport corridors under adverse propagation conditions.
Simulation results demonstrate that the proposed adaptive scheme demonstrates notable improvements over classical loss-based and delay-based baselines in reducing queuing delays at UAV relay nodes, enhances the transmission efficiency of multi-hop terminals, and effectively maintains end-to-end goodput stability in high-latency environments.
L. Zong, Yun Cheng, Yi Yao· Italian National Conference...· 0 citations
Deploying uncrewed aerial vehicles (UAVs) in vehicular networks overcomes the inherent limitations of terrestrial infrastructure by dynamically enhancing coverage and line-of-sight (LoS) connectivity. However, further enhancement of the data rate necessitates the deployment of additional terrestrial base stations (BSs) and UAVs, which incur high costs and consume a large amount of energy. To address these challenges, synergistically integrating UAVs equipped with intelligent reflecting surfaces (IRS) and multiple-input multiple-output (MIMO) techniques can effectively improve the channel capacity of air-to-ground integrated vehicular networks, while maintaining low cost and low power consumption. The key idea is to partially replace some of the required terrestrial relays with high-flexibility and energy-efficient UAVs equipped with IRS. Specifically, in IRS-MIMO air-to-ground integrated vehicular networks, we formulate a joint precoding design, phase shift optimization, and UAV deployment problem with the objective of maximizing the weighted sum-rate. To tackle this non-convex problem, an iterative optimization algorithm with polynomial-time complexity is developed, which enables a gradual approximation of a feasible solution to the formulated problem. Finally, simulation results demonstrate that the proposed scheme is superior to the state-of-the-art schemes in terms of the weighted sum-rate. Additionally, the impact of network parameters on transmission performance and the convergence of iterative optimization are thoroughly analyzed.
Yi-Xin He, Fang-Hui Huang, Da-Wei Wang et al.· IEEE Transactions on Communi...· 0 citations
Simulation results demonstrate that RESCUE-ISAC improves energy efficiency, link reliability, sensing performance, mobility robustness, and runtime–performance trade-off compared with heuristic, lightweight, and optimization-based benchmark schemes.
R. Khalil, Saba Mahmood, T. Jan et al.· IEEE Open Journal of Vehicul...· 0 citations
The space-air-ground-sea integrated networks (SAGSIN) are anticipated to provide seamless and ubiquitous connectivity in remote areas with deficient infrastructure. Nevertheless, the downlink communication to remote unmanned aerial vehicle (UAV) swarms remains challenged due to ultralong-distance propagation, high mobility, and the deficiency of infrastructure. To address these challenges, this paper introduces a multi-satellite cooperative downlink system assisted by a reconfigurable intelligent surface (RIS), strategically mounted on an unmanned aerial aircraft carrier (UAAC). Through this innovative configuration, the signal propagation environment between satellites and UAV swarms can be intelligently reconfigured. Integrating multi-satellite cooperative diversity and RISreconfigured propagation, the system optimizes the communication performance within the constraints of satellite power. A joint optimization problem aimed at maximizing the total downlink sum rate is formulated, through the cooperative design of satellite beamforming vectors and RIS phase shifts. To efficiently solve this non-convex problem, an alternating optimization (AO)-based algorithm is developed, which alternately applies the weighted minimum mean square error (WMMSE) algorithm for beamforming and manifold optimization (MO) method for phase shift design. Comprehensive simulations indicate substantial performance enhancements over baselines.
Yu-Ze Tong, Shao-Hua Wu, Qun Wang et al.· 2026 IEEE/CIC International...· 0 citations
Integrated satellite–aerial networks (ISANs) are emerging as a promising architecture that combines high-throughput inter-satellite transmission with the agility of uncrewed aerial vehicles (UAVs) to support flexible and low-latency traffic delivery. Owing to the inherently uneven traffic distribution in the satellite layer, traffic flows often suffer from congestion and excessive multi-hop forwarding delays. UAVs can act as adaptive relays to offload congested traffic and mitigate routing detours, thereby reducing end-to-end latency. However, latency-aware traffic management in ISANs is fundamentally challenged by highly dynamic satellite topologies, heterogeneous link characteristics, and the tight coupling between satellite traffic dynamics and UAV mobility. Existing approaches often suffer from cross-layer misalignment between satellite routing and aerial relaying, which limits coordinated latency adaptation. To address these challenges, this paper proposes an agentic UAV-assisted relay framework, termed DUS-SACUD, in which an autonomous UAV acts as an embodied agent that proactively steers traffic. First, a graph-conditioned diffusion model is developed for generative UAV–satellite link (USL) selection under dynamic network states. Second, a soft actor–critic-based reinforcement learning scheme is employed for embodied UAV deployment to minimize USL-induced delay. Through closed-loop alternating execution, DUS-SACUD jointly optimizes connectivity adaptation and mobility control in ISANs. Extensive simulations based on a realistic satellite constellation demonstrate significant end-to-end latency reduction over existing routing and UAV-assisted baselines, while maintaining robust performance under diverse ISAN conditions.
Xintong Li, Feng Wang, Qi Wu et al.· IEEE Transactions on Cogniti...· 0 citations
An unmanned aerial vehicle (UAV)-enabled ISAC system employing rate-splitting multiple access (RSMA) and a joint beamforming and trajectory optimization framework is investigated and results demonstrate that the proposed algorithm significantly improves the achievable system downlink rate.
Shunxuan Wang, Qi Zhu· Italian National Conference...· 0 citations
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