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Search Results (427)

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Keywords = air channel modeling

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20 pages, 2352 KiB  
Article
Three-Dimensional Physics-Based Channel Modeling for Fluid Antenna System-Assisted Air–Ground Communications by Reconfigurable Intelligent Surfaces
by Yuran Jiang and Xiao Chen
Electronics 2025, 14(15), 2990; https://doi.org/10.3390/electronics14152990 - 27 Jul 2025
Viewed by 187
Abstract
Reconfigurable intelligent surfaces (RISs), recognized as one of the most promising key technologies for sixth-generation (6G) mobile communications, are characterized by their minimal energy expenditure, cost-effectiveness, and straightforward implementation. In this study, we develop a novel communication channel model that integrates RIS-enabled base [...] Read more.
Reconfigurable intelligent surfaces (RISs), recognized as one of the most promising key technologies for sixth-generation (6G) mobile communications, are characterized by their minimal energy expenditure, cost-effectiveness, and straightforward implementation. In this study, we develop a novel communication channel model that integrates RIS-enabled base stations with unmanned ground vehicles. To enhance the system’s adaptability, we implement a fluid antenna system (FAS) at the unmanned ground vehicle (UGV) terminal. This innovative model demonstrates exceptional versatility across various wireless communication scenarios through the strategic adjustment of active ports. The inherent dynamic reconfigurability of the FAS provides superior flexibility and adaptability in air-to-ground communication environments. In the paper, we derive and study key performance characteristics like the autocorrelation function (ACF), validating the model’s effectiveness. The results demonstrate that the RIS-FAS collaborative scheme significantly enhances channel reliability while effectively addressing critical challenges in 6G networks, including signal blockage and spatial constraints in mobile terminals. Full article
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14 pages, 38692 KiB  
Article
Development of a Microscale Urban Airflow Modeling System Incorporating Buildings and Terrain
by Hyo-Been An and Seung-Bu Park
Atmosphere 2025, 16(8), 905; https://doi.org/10.3390/atmos16080905 - 25 Jul 2025
Viewed by 145
Abstract
We developed a microscale airflow modeling system with detailed building and terrain data to better understand the urban microclimate. Building shapes and heights, and terrain elevation data were integrated to construct a high-resolution urban surface geometry. The system, based on computational fluid dynamics [...] Read more.
We developed a microscale airflow modeling system with detailed building and terrain data to better understand the urban microclimate. Building shapes and heights, and terrain elevation data were integrated to construct a high-resolution urban surface geometry. The system, based on computational fluid dynamics using OpenFOAM, can resolve complex flow structures around built environments. Inflow boundary conditions were generated using logarithmic wind profiles derived from Automatic Weather System (AWS) observations under neutral stability. After validation with wind-tunnel data for a single block, the system was applied to airflow modeling around a university campus in Seoul using AWS data from four nearby stations. The results demonstrated that the system captured key flow characteristics such as channeling, wake, and recirculation induced by complex terrain and building configurations. In particular, easterly inflow cases with high-rise buildings on the leeward side of a mountain exhibited intensified wakes and internal recirculations, with elevated centers influenced by tall structures. This modeling framework, with further development, could support diverse urban applications for microclimate and air quality, facilitating urban resilience. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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19 pages, 1307 KiB  
Article
Three-Dimensional Non-Stationary MIMO Channel Modeling for UAV-Based Terahertz Wireless Communication Systems
by Kai Zhang, Yongjun Li, Xiang Wang, Zhaohui Yang, Fenglei Zhang, Ke Wang, Zhe Zhao and Yun Wang
Entropy 2025, 27(8), 788; https://doi.org/10.3390/e27080788 - 25 Jul 2025
Viewed by 174
Abstract
Terahertz (THz) wireless communications can support ultra-high data rates and secure wireless links with miniaturized devices for unmanned aerial vehicle (UAV) communications. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic channel model (GSCM) is proposed for multiple-input multiple-output (MIMO) communication links between [...] Read more.
Terahertz (THz) wireless communications can support ultra-high data rates and secure wireless links with miniaturized devices for unmanned aerial vehicle (UAV) communications. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic channel model (GSCM) is proposed for multiple-input multiple-output (MIMO) communication links between the UAVs in the THz band. The proposed channel model considers not only the 3D scattering and reflection scenarios (i.e., reflection and scattering fading) but also the atmospheric molecule absorption attenuation, arbitrary 3D trajectory, and antenna arrays of both terminals. In addition, the statistical properties of the proposed GSCM (i.e., the time auto-correlation function (T-ACF), space cross-correlation function (S-CCF), and Doppler power spectrum density (DPSD)) are derived and analyzed under several important UAV-related parameters and different carrier frequencies, including millimeter wave (mmWave) and THz bands. Finally, the good agreement between the simulated results and corresponding theoretical ones demonstrates the correctness of the proposed GSCM, and some useful observations are provided for the system design and performance evaluation of UAV-based air-to-air (A2A) THz-MIMO wireless communications. Full article
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18 pages, 6313 KiB  
Article
Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment
by Yong Pan, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong and Hang Xiao
Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883 - 18 Jul 2025
Viewed by 232
Abstract
In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory [...] Read more.
In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning. Full article
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
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25 pages, 693 KiB  
Article
Distributed Interference-Aware Power Optimization for Multi-Task Over-the-Air Federated Learning
by Chao Tang, Dashun He and Jianping Yao
Telecom 2025, 6(3), 51; https://doi.org/10.3390/telecom6030051 - 14 Jul 2025
Viewed by 198
Abstract
Over-the-air federated learning (Air-FL) has emerged as a promising paradigm that integrates communication and learning, which offers significant potential to enhance model training efficiency and optimize communication resource utilization. This paper addresses the challenge of interference management in multi-cell Air-FL systems, focusing on [...] Read more.
Over-the-air federated learning (Air-FL) has emerged as a promising paradigm that integrates communication and learning, which offers significant potential to enhance model training efficiency and optimize communication resource utilization. This paper addresses the challenge of interference management in multi-cell Air-FL systems, focusing on parallel multi-task scenarios where each cell independently executes distinct training tasks. We begin by analyzing the impact of aggregation errors on local model performance within each cell, aiming to minimize the cumulative optimality gap across all cells. To this end, we formulate an optimization framework that jointly optimizes device transmit power and denoising factors. Leveraging the Pareto boundary theory, we design a centralized optimization scheme that characterizes the trade-offs in system performance. Building upon this, we propose a distributed power control optimization scheme based on interference temperature (IT). This approach decomposes the globally coupled problem into locally solvable subproblems, thereby enabling each cell to adjust its transmit power independently using only local channel state information (CSI). To tackle the non-convexity inherent in these subproblems, we first transform them into convex problems and then develop an analytical solution framework grounded in Lagrangian duality theory. Coupled with a dynamic IT update mechanism, our method iteratively approximates the Pareto optimal boundary. The simulation results demonstrate that the proposed scheme outperforms baseline methods in terms of training convergence speed, cross-cell performance balance, and test accuracy. Moreover, it achieves stable convergence within a limited number of iterations, which validates its practicality and effectiveness in multi-task edge intelligence systems. Full article
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28 pages, 3719 KiB  
Article
FF-YOLO: An Improved YOLO11-Based Fatigue Detection Algorithm for Air Traffic Controllers
by Shijie Tan, Weijun Pan, Leilei Deng, Qinghai Zuo and Yao Zheng
Appl. Sci. 2025, 15(13), 7503; https://doi.org/10.3390/app15137503 - 3 Jul 2025
Viewed by 380
Abstract
Real-time detection of fatigue states in air traffic controllers (ATCOs) is crucial for ensuring air traffic safety. Existing methods exhibit limitations such as poor real-time performance, intrusiveness, and susceptibility to lighting and occlusion. This paper proposes FF-YOLO, an improved YOLO11-based deep learning algorithm, [...] Read more.
Real-time detection of fatigue states in air traffic controllers (ATCOs) is crucial for ensuring air traffic safety. Existing methods exhibit limitations such as poor real-time performance, intrusiveness, and susceptibility to lighting and occlusion. This paper proposes FF-YOLO, an improved YOLO11-based deep learning algorithm, to detect ATCO fatigue states through facial feature analysis. A custom dataset comprising 25,154 facial images collected from 10 ATCOs was constructed for model training and validation. The FF-YOLO model introduces the CA-C3K2 module for fine-grained feature extraction under complex lighting, incorporates a spatial–channel attention mechanism for improved detection accuracy during occlusion, and MPDIoU loss for enhanced accuracy on multi-scale facial images with accelerated convergence. Experimental results show FF-YOLO achieves 94.2% mAP@50, 74.7% mAP@50–95, 83.8% precision, and 73.8% recall, with gains of +13.7%, +11.6%, +0.6%, and +5.9% over YOLO11n, respectively, thereby enabling real-time and accurate detection of ATCO fatigue states. Future work will expand datasets with larger and more diverse ATCO populations to enhance generalizability. Full article
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28 pages, 1210 KiB  
Article
A Multi-Ray Channel Modelling Approach to Enhance UAV Communications in Networked Airspace
by Fawad Ahmad, Muhammad Yasir Masood Mirza, Iftikhar Hussain and Kaleem Arshid
Inventions 2025, 10(4), 51; https://doi.org/10.3390/inventions10040051 - 1 Jul 2025
Cited by 1 | Viewed by 414
Abstract
In recent years, the use of unmanned aerial vehicles (UAVs), commonly known as drones, has significantly surged across civil, military, and commercial sectors. Ensuring reliable and efficient communication between UAVs and between UAVs and base stations is challenging due to dynamic factors such [...] Read more.
In recent years, the use of unmanned aerial vehicles (UAVs), commonly known as drones, has significantly surged across civil, military, and commercial sectors. Ensuring reliable and efficient communication between UAVs and between UAVs and base stations is challenging due to dynamic factors such as altitude, mobility, environmental obstacles, and atmospheric conditions, which existing communication models fail to address fully. This paper presents a multi-ray channel model that captures the complexities of the airspace network, applicable to both ground-to-air (G2A) and air-to-air (A2A) communications to ensure reliability and efficiency within the network. The model outperforms conventional line-of-sight assumptions by integrating multiple rays to reflect the multipath transmission of UAVs. The multi-ray channel model considers UAV flights’ dynamic and 3-D nature and the conditions in which UAVs typically operate, including urban, suburban, and rural environments. A technique that calculates the received power at a target UAV within a networked airspace is also proposed, utilizing the reflective characteristics of UAV surfaces along with the multi-ray channel model. The developed multi-ray channel model further facilitates the characterization and performance evaluation of G2A and A2A communications. Additionally, this paper explores the effects of various factors, such as altitude, the number of UAVs, and the spatial separation between them on the power received by the target UAV. The simulation outcomes are validated by empirical data and existing theoretical models, providing comprehensive insight into the proposed channel modelling technique. Full article
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18 pages, 4683 KiB  
Article
Transmission of LG Modes in High-Capacity 16 × 10 Gbps FSO System Using FBG Sensors Under Different Channel Scenarios
by Meet Kumari and Satyendra K. Mishra
Micromachines 2025, 16(7), 738; https://doi.org/10.3390/mi16070738 - 24 Jun 2025
Viewed by 557
Abstract
Free space optics (FSO) aims to perform as one of the best optical wireless channels to design a reliable, flexible, and cost-effective communication system. In FSO systems, mode-division multiplexing (MDM) transmission is a proven technique to expand transmission capacity per communication link. Thus, [...] Read more.
Free space optics (FSO) aims to perform as one of the best optical wireless channels to design a reliable, flexible, and cost-effective communication system. In FSO systems, mode-division multiplexing (MDM) transmission is a proven technique to expand transmission capacity per communication link. Thus, a 16 × 10 Gbps MDM-FSO system using fiber Bragg grating (FBG) sensors for the coexistence of communication and sensing, exploiting FSO links to transmit distinct Laguerre-Gaussian (LG) beams at a 1000–1900 m range, is proposed. The results illustrate that the system can transmit higher-order LG beams with sensor temperatures of 20–120 °C over a 1500 m range under clear air, drizzle, and moderate haze weather. Also, an improved performance is achieved in gamma–gamma compared to the log-normal distribution model for 10−6–10−2.5 index modulation under weak-to-strong turbulence. The proposed system is capable of offering a high optical signal-to-noise ratio (OSNR) and gain of 113.39 and 15.43 dB, respectively, at an aggregate data rate of 160 Gbps under different atmospheric scenarios. Moreover, the proposed system achieves better system performance compared to existing works. Full article
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28 pages, 7907 KiB  
Article
Transformer-Based Air-to-Ground mmWave Channel Characteristics Prediction for 6G UAV Communications
by Borui Huang, Zhichao Xin, Fan Yang, Yuyang Zhang, Yu Liu, Jie Huang and Ji Bian
Sensors 2025, 25(12), 3731; https://doi.org/10.3390/s25123731 - 14 Jun 2025
Viewed by 461
Abstract
With the increasing development of 6th-generation (6G) air-to-ground (A2G) communications, the combination of millimeter-wave (mmWave) and multiple-input multiple-output (MIMO) technologies can offer unprecedented bandwidth and capacity for unmanned aerial vehicle (UAV) communications. The introduction of new technologies will also make the UAV channel [...] Read more.
With the increasing development of 6th-generation (6G) air-to-ground (A2G) communications, the combination of millimeter-wave (mmWave) and multiple-input multiple-output (MIMO) technologies can offer unprecedented bandwidth and capacity for unmanned aerial vehicle (UAV) communications. The introduction of new technologies will also make the UAV channel characteristics more complex and variable, posing higher requirements for UAV channel modeling. This paper presents a novel predictive channel modeling method based on Transformer architecture by integrating data-driven approaches with UAV air-to-ground channel modeling. By introducing the mmWave and MIMO into UAV communications, the channel data of UAVs at various flight altitudes is first collected. Based on the Transformer network, the typical UAV channel characteristics, such as received power, delay spread, and angular spread, are then predicted and analyzed. The results indicate that the proposed predictive method exhibits excellent performance in prediction accuracy and stability, effectively addressing the complexity and variability of channel characteristics caused by mmWave bands and MIMO technology. This method not only provides strong support for the design and optimization of future 6G UAV communication systems but also lays a solid communication foundation for the widespread application of UAVs in intelligent transportation, logistics, and other fields in the future. Full article
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33 pages, 13448 KiB  
Article
Analysis of Congestion-Propagation Time-Lag Characteristics in Air Route Networks Based on Multi-Channel Attention DSNG-BiLSTM
by Yue Lv, Yong Tian, Xiao Huang, Haifeng Huang, Bo Zhi and Jiangchen Li
Aerospace 2025, 12(6), 529; https://doi.org/10.3390/aerospace12060529 - 11 Jun 2025
Viewed by 346
Abstract
As air transportation demand continues to rise, congestion in air route networks has seriously compromised the safe and efficient operation of air traffic. Few studies have examined the spatiotemporal characteristics of congestion propagation under different time lag conditions. To address this gap, this [...] Read more.
As air transportation demand continues to rise, congestion in air route networks has seriously compromised the safe and efficient operation of air traffic. Few studies have examined the spatiotemporal characteristics of congestion propagation under different time lag conditions. To address this gap, this study proposes a cross-segment congestion-propagation causal time-lag analysis framework. First, to account for the interdependency across segments in air route networks, we construct a point–line congestion state assessment model and introduce the FCM-WBO algorithm for precise congestion state identification. Next, the Multi-Channel Attention DSNG-BiLSTM model is designed to estimate the causal weights of congestion propagation between segments. Finally, based on these causal weights, two indicators—CPP and CPF—are derived to analyze the spatiotemporal characteristics of congestion propagation under various time lag levels. The results indicate that our method achieves over 90% accuracy in estimating causal weights. Moreover, the propagation features differ significantly in their spatiotemporal distributions under different time lags. Spatially, congestion sources tend to spread as time lag increases. We also identify segments that are likely to become overloaded, which serve as the primary receivers of congestion. Temporally, analysis of time-lag features reveals that because of higher traffic flow during peak periods, congestion propagates 36.92% more slowly than during the early-morning hours. By analyzing congestion propagation at multiple time lags, controllers can identify potential congestion sources in advance. They can then implement targeted interventions during critical periods, thereby alleviating congestion in real time and improving route-network efficiency and safety. Full article
(This article belongs to the Section Air Traffic and Transportation)
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13 pages, 2673 KiB  
Article
Longitudinal Ceiling Temperature Profile in an Inclined Channel Induced by a Wall-Attached Fire
by Xubo Huang, Yongfeng Zhang, Wei Wang and Zhenxiang Tao
Fire 2025, 8(6), 222; https://doi.org/10.3390/fire8060222 - 31 May 2025
Viewed by 920
Abstract
Channel fire poses a great threat to personnel safety and structural strength, in which the temperature profile is worthy of attention. In this paper, the longitudinal temperature profile of a ceiling jet induced by a wall-attached fire with different channel slopes was experimentally [...] Read more.
Channel fire poses a great threat to personnel safety and structural strength, in which the temperature profile is worthy of attention. In this paper, the longitudinal temperature profile of a ceiling jet induced by a wall-attached fire with different channel slopes was experimentally investigated using a 1:8 reduced-scale channel. The results show the following: (1) For channel fire with a horizontal ceiling, the influence of the burner aspect ratio and source-ceiling height on the temperature profile is monotonous in the cases considered in this work. With a larger burner aspect ratio and larger source-ceiling distance, more ambient air could be entrained; hence, the longitudinal temperature under the ceiling decays faster. (2) For channel fire with an inclined ceiling, when the burner aspect ratio and source-ceiling distance remain constant, the asymmetric entrainment induced by the flame under larger channel slope leads to more hot smoke being transported upstream. Consequently, the temperature profile is not symmetric, with higher temperatures upstream and lower temperatures downstream. (3) Combining the influence of the burner aspect ratios, source-ceiling distance, and burner aspect ratio, the characteristic length scale was modified. Based on this, a model describing the ceiling temperature profile was proposed and then verified with previous data. Full article
(This article belongs to the Special Issue Advances in Fire Science and Fire Protection Engineering)
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23 pages, 4015 KiB  
Article
Performance Analysis of FSO-UWOC Mixed Dual-Hop Relay System with Decode-and-Forward Protocol
by Yu Zhou, Yueheng Li, Meiyan Ju and Yong Lv
Electronics 2025, 14(11), 2227; https://doi.org/10.3390/electronics14112227 - 30 May 2025
Viewed by 354
Abstract
This study investigates the performance of a mixed dual-hop free-space optical/underwater wireless optical communication (FSO-UWOC) system employing a decode-and-forward (DF) relay protocol, particularly under a comprehensive hybrid channel fading model. The FSO link is assumed to experience Gamma–Gamma atmospheric turbulence fading, combined with [...] Read more.
This study investigates the performance of a mixed dual-hop free-space optical/underwater wireless optical communication (FSO-UWOC) system employing a decode-and-forward (DF) relay protocol, particularly under a comprehensive hybrid channel fading model. The FSO link is assumed to experience Gamma–Gamma atmospheric turbulence fading, combined with air path loss and pointing errors. Meanwhile, the UWOC link is modeled with generalized Gamma distribution (GGD) oceanic turbulence fading, along with underwater path loss and pointing errors. Based on the proposed hybrid channel fading model, closed-form expressions for the average outage probability (OP) and average bit error rate (BER) of the mixed dual-hop system are derived using the higher transcendental Meijer-G function. Similarly, the closed-form expression for the average ergodic capacity of the mixed relay system is obtained via the bivariate Fox-H function. Additionally, asymptotic performance analyses for the average outage probability and BER under high signal-to-noise ratio (SNR) conditions are provided. Finally, Monte Carlo simulations are conducted to validate the accuracy of the derived theoretical expressions and to illustrate the effects of key system parameters on the performance of the mixed relay FSO-UWOC system. Full article
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31 pages, 8088 KiB  
Article
Communication Infrastructure Design for Reliable UAV Operations in Air Mobility Corridors
by Igor Kabashkin, Duman Iskakov, Roman Topilskiy, Gulnar Tlepiyeva, Timur Sultanov and Zura Sansyzbayeva
Drones 2025, 9(6), 401; https://doi.org/10.3390/drones9060401 - 29 May 2025
Viewed by 801
Abstract
The integration of unmanned aerial vehicles (UAVs) into urban air mobility (UAM) systems necessitates reliable and uninterrupted communication infrastructure to ensure safety, control, and data continuity within designated air corridors. This paper proposes and evaluates four radio repeater deployment strategies to support robust [...] Read more.
The integration of unmanned aerial vehicles (UAVs) into urban air mobility (UAM) systems necessitates reliable and uninterrupted communication infrastructure to ensure safety, control, and data continuity within designated air corridors. This paper proposes and evaluates four radio repeater deployment strategies to support robust UAV communication in urban environments: Strategy 1 with non-overlapping radio coverage, Strategy 2 with fully overlapping coverage zones, Strategy 3 with alternating redundancy between repeater pairs, and Strategy 4 with full duplication of overlapping coverage. A continuous-time Markov modeling approach is employed to quantify communication availability under varying traffic loads and failure conditions. The strategies are assessed based on infrastructure requirements, reliability performance, and suitability for segmented and non-linear corridor geometries. The results show that increasing redundancy significantly improves reliability: for example, channel unavailability drops from 35% under Strategy 1 (no redundancy) to less than 0.5% under Strategy 4 (full duplication). Strategy 3 achieves a balanced performance, maintaining unavailability below 1% with approximately 50% fewer resources than Strategy 4. A case study in the Greenline district of Astana, Kazakhstan, illustrates the practical application of the framework, demonstrating how hybrid deployment strategies can address different operational and environmental demands. The results show that increasing redundancy significantly enhances availability, with Strategy 3 offering the most efficient balance between reliability and resource use. The proposed methodology provides a scalable foundation for designing resilient UAV communication systems to support future urban airspace operations. Full article
(This article belongs to the Section Innovative Urban Mobility)
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25 pages, 11422 KiB  
Article
ESCI: An End-to-End Spatiotemporal Correlation Integration Framework for Low-Observable Extended UAV Tracking with Cascade MIMO Radar Subject to Mixed Interferences
by Guanzheng Hu, Xin Fang, Darong Huang and Zhenyuan Zhang
Electronics 2025, 14(11), 2181; https://doi.org/10.3390/electronics14112181 - 27 May 2025
Viewed by 423
Abstract
Continuous and robust trajectory tracking of unmanned aerial vehicles (UAVs) plays a crucial role in urban air transportation systems. Accordingly, this article presents an end-to-end spatiotemporal correlation integration (ESCI)-based UAV tracking framework by leveraging a high-resolution cascade multiple input multiple output (MIMO) radar. [...] Read more.
Continuous and robust trajectory tracking of unmanned aerial vehicles (UAVs) plays a crucial role in urban air transportation systems. Accordingly, this article presents an end-to-end spatiotemporal correlation integration (ESCI)-based UAV tracking framework by leveraging a high-resolution cascade multiple input multiple output (MIMO) radar. On this account, a novel joint anti-interference detection and tracking system for weak extended targets is presented in this paper; the proposed method handles them jointly by integrating a continuous detection process into tracking. It not only eliminates the threshold decision-making process to avoid the loss of weak target information, but also significantly reduces the interference from other co-channel radars and strong clutters by exploring the spatiotemporal correlations within a sequence of radar frames, thereby improving the detectability of weak targets. In addition, to accommodate the time-varying number and extended size of radar reflections, with the ellipse spatial probability distribution model, the extended UAV with multiple scattering sources can be treated as an entity to track, and the complex measurement-to-object association procedure can be avoided. Finally, with Texas Instruments AWR2243 (TI AWR2243) we can utilize a cascade frequency-modulated continuous wave–multiple input multiple output (FMCW-MIMO) radar platform. The results show that the proposed method can obtain outstanding anti-interference performance for extended UAV tracking compared with state-of-the-art methods. Full article
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33 pages, 2545 KiB  
Review
Research Progress on Modulation Format Recognition Technology for Visible Light Communication
by Shengbang Zhou, Weichang Du, Chuanqi Li, Shutian Liu and Ruiqi Li
Photonics 2025, 12(5), 512; https://doi.org/10.3390/photonics12050512 - 19 May 2025
Cited by 1 | Viewed by 559 | Correction
Abstract
As sixth-generation mobile communication (6G) advances towards ultra-high speed and global coverage, visible light communication (VLC) has emerged as a crucial complementary technology due to its ultra-high bandwidth, low power consumption, and immunity to electromagnetic interference. Modulation format recognition (MFR) plays a vital [...] Read more.
As sixth-generation mobile communication (6G) advances towards ultra-high speed and global coverage, visible light communication (VLC) has emerged as a crucial complementary technology due to its ultra-high bandwidth, low power consumption, and immunity to electromagnetic interference. Modulation format recognition (MFR) plays a vital role in the dynamic optimization and adaptive transmission of VLC systems, significantly influencing communication performance in complex channel environments. This paper systematically reviews the research progress in MFR for VLC, comparing the theoretical frameworks and limitations of traditional likelihood-based (LB) and feature-based (FB) methods. It also explores the advancements brought by deep learning (DL) technology, particularly in enhancing noise robustness, classification accuracy, and cross-scenario adaptability through automatic feature extraction and nonlinear mapping. The findings indicate that DL-based MFR substantially enhances recognition performance in intricate channels via multi-dimensional feature fusion, lightweight architectures, and meta-learning paradigms. Nonetheless, challenges remain, including high model complexity and a strong reliance on labeled data. Future research should prioritize multi-domain feature fusion, interdisciplinary collaboration, and hardware–algorithm co-optimization to develop lightweight, high-precision, and real-time MFR technologies that align with the 6G vision of space–air–ground–sea integrated networks. Full article
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