Aug 2026· Italian National Conference on Sensors· Vol 26· 0 citations· 30 references
Medicine
TL;DR
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.
Abstract
Driven by the vision of sixth-generation (6G) communication networks, Space–Air–Ground Integrated Vehicular Networks (SAGVNs) address the connectivity blind spots inherent in traditional networks by integrating unmanned aerial vehicles (UAVs) as highly mobile relay nodes. However, the high bit error rates (BERs) and prolonged propagation delays characteristic of satellite links, coupled with the highly dynamic topologies and multi-hop transmission nature of UAVs and terrestrial vehicles, present significant challenges to reliable end-to-end data streaming. To mitigate the performance degradation caused by link asymmetries in heterogeneous networks, this paper proposes a reliable transmission optimization scheme for UAV-relayed SAGVNs. By comprehensively modeling the transmission dynamics of long-delay, high-BER satellite links and mobile multi-hop UAV networks, the proposed scheme introduces an enhanced slow-start mechanism to accelerate throughput growth, thereby mitigating the startup lag induced by extensive propagation delays. Furthermore, an accurate packet loss differentiation model is established during the congestion avoidance phase. This model effectively decouples non-congestion packet losses—triggered by random channel errors or topology handovers due to high-speed node mobility—from genuine congestion-induced losses caused by buffer overflows at bottleneck nodes. 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.
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
This paper investigates the use of unmanned aerial vehicles (UAVs) as flying base stations (BSs) to enhance fifth generation (5G) vehicular communications on highways, where traffic congestion and fluctuating user demand can challenge the capacity of terrestrial infrastructure. While UAV-assisted vehicular networking has attracted significant attention, many existing studies rely on simplified mobility, propagation, or communication models that limit the assessment of practical deployment performance. To address these limitations, we develop a realistic UAV-assisted vehicular networking framework that integrates microscopic traffic simulation through Simulation of Urban MObility (SUMO), network control via Traffic Control Interface (TraCI), and standard-compliant 5G communication modeling using MATLAB R2025b 5G Toolbox. The framework incorporates a 3rd Generation Partnership Project (3GPP) rural macro cell (RMa) highway scenario, detailed clustered delay line (CDL)-based channel characterization, and cross-layer communication procedures. Within this framework, we propose a low-complexity trajectory optimization strategy that adapts the UAV position in real time to maximize the average received signal to noise ratio (SNR) while respecting practical motion constraints. Simulation results demonstrate that adaptive UAV positioning enhances communication performance, achieving mean SNR gains of up to 2.04 dB, throughput improvement of up to 11.2%, and block error rate (BLER) reductions of up to 27.3%. These findings highlight the potential of UAV-assisted communications to enhance user-perceived quality of service (QoS) for bandwidth-demanding vehicular applications under realistic 5G highway operating conditions.
Ignacio Vidal, Sandy Bolufé, K. Toledo· Italian National Conference...· 0 citations
Unmanned aerial vehicles (UAVs) have emerged as promising aerial platforms for next-generation wireless networks, offering three-dimensional mobility, rapid deployment, and high line-of-sight (LoS) link probability. This paper presents a structured overview of UAV-assisted wireless communications, covering key network architectures, air-to-ground channel characteristics, mobility-aware deployment and trajectory design, resource management, and multi-UAV cooperation. We further review recent integrations of UAVs with emerging technologies such as artificial intelligence (AI)-driven optimization, reconfigurable intelligent surface (RIS), integrated sensing and communication (ISAC), multiple-input multiple-output (MIMO), and semantic communication. Integration scenarios and recent research trends in beyond-5G and 6G networks are discussed, and open challenges along with future research directions are identified. This survey aims to provide a concise yet comprehensive reference for researchers and engineers working on UAV-assisted wireless network design.
Jueun Jeong, Sehyeon Kwon, Changhui Kim et al.· International Conference on...· 0 citations
The evolution of sixth-generation (6G) networks increasingly demands seamless and reliable connectivity across heterogeneous and geographically dispersed environments, with maritime regions remaining a major challenge due to vast coverage areas, limited terrestrial infrastructure, and complex propagation conditions. In this paper, we investigate the capacity characteristics of space-air-ground-sea integrated networks (SAGSINs) for maritime communications. Specifically, we consider a SAGSIN system comprising a terrestrial base station (BS), a geostationary satellite, a decode-and-forward (DF) relay, and maritime users randomly distributed according to a Poisson point process (PPP). The relay, implemented by either an uncrewed aerial vehicle (UAV) or a large ship, serves multiple maritime users, providing a unified framework for comparing heterogeneous relay platforms and backhaul options. Based on this model, the system performance is analyzed under two representative fading regimes: 1) quasi-static fading, where analytical expressions and tight upper bounds are derived for the outage probability and corresponding outage capacity; and 2) block fading, where closed-form ergodic capacity formulations are obtained to evaluate the long-term average throughput. Extensive Monte Carlo simulations validate the theoretical analysis and quantify the effects of key system parameters. Our results offer insights into the design and optimization of high-reliability maritime communication links, providing guidelines for practical implementation and future 6G SAGSINs development.
Jinpeng Xu, Yingqi He, Lin Zhou et al.· IEEE Transactions on Wireles...· 0 citations
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.
H. V. Cuu, L. Huynh, Ž. Koboević· Automation· 0 citations
Millimeter-wave (mmWave) vehicular-to-everything (V2X) links are highly vulnerable to sudden blockages in dense urban traffic. Since terrestrial roadside links can degrade rapidly, and alternative ground paths are often limited, maintaining reliable service with only ground networking resources remains challenging. To enhance link reliability by exploiting aerial relay resources in air–ground integrated networks, this paper proposes a vision-assisted unmanned aerial vehicle (UAV) relay triggering framework. The framework uses roadside multi-camera images to predict the future link state of a target vehicle and triggers a UAV decode-and-forward (DF) relay before the direct roadside-unit (RSU)–vehicle link becomes unreliable. To enable target-specific prediction, a template-guided image-matching module is developed to localize the target vehicle in multi-view images. The matched features are fused and temporally modeled to predict future LoS, NLoS, and Absent states, with the predicted NLoS probability further used to determine the UAV activation decision through a probability-based triggering policy. Simulation results on a 3D ray-tracing urban V2X dataset show that the proposed dual-view predictor achieves about 99% validation accuracy, compared with about 87% for the single-view baseline. The proposed relay triggering scheme reduces the outage probability from 15.08% for RSU-only transmission and 4.49% for reactive relaying to 0.76%, and improves the 5th-percentile rate from 11.72 Mbps to 22.49 Mbps over reactive relaying.
Yicheng Wang, Weiyan Chen, Luting Kong et al.· Italian National Conference...· 0 citations