Height Of Unmanned Aerial Vehicle Research Articles

A three‐dimensional wideband mmWave multiple‐input multiple‐output channel model for aerial reconfigurable intelligent surface‐assisted communication systems

SummaryThis paper presents a wideband millimeter wave (mmWave) channel model for aerial reconfigurable intelligent surface (ARIS) communications, in which the reconfigurable intelligent surface (RIS) is attached to an unmanned aerial vehicle (UAV) to enable intelligent signal reflections in the air. The model is established according to standard 3GPP channel models and considers important propagation factors, for example, large‐scale fading, small‐scale fading, and radiation pattern of reflection units (RUs). In addition, the model assumes three‐dimensional (3D) rotations of RIS and can capture its effects on channel characteristics. Based on the model, we propose a design method for RIS reflection phases. Statistics including channel amplitude, spatial, temporal, and frequency correlation functions (CFs), and space‐Doppler power spectral density (SD‐PSD) are obtained. The impacts of RU number, UAV height and speed, and RIS rotation on channel statistics are investigated. Results suggest that the designed reflection phases can effectively mitigate multipath fading and Doppler effect. Compared to the yaw angle of the UAV platform, channel characteristics are more sensitive to the roll and pitch angles.

Development and Analysis of Outage Probability and Achievable Rate for UAV Relay Implementation in Disaster Areas

Unmanned aerial vehicles (UAV) coupled with wireless networks have offered the potential for forthcoming mobile communications networks. The UAV-assisted wireless communication technology approach is an option for maintaining communication services, one of which is for disaster areas. This study aims to investigate the deployment of UAV-assisted communications in disaster areas. The simulation in this work is focused on investigating the relationship between the UAV’s height or radius and the outage probability and achievable rate. We identifies a UAV that behaves as a relay in a disaster area connected to two users, identified several critical parameters, such as UAV height, radius, and SNR value, and investigated the impact of changing each of them on outage probability and achievable rate values. Finally, we simulates the effect of these critical parameters on outage probability and achievable rate to maximize the use of UAV-assisted communication as a disaster management solution. According to the simulation results, as the signal to noise (SNR) increases, the probability of network communication interference decreases, and the achievable level increases. Moreover, increasing the range of UAVs can improve communication performance by reducing the probability of outages and increasing the achievable rate.

Aerial Bridge: A Secure Tunnel Against Eavesdropping in Terrestrial-Satellite Networks

Terrestrial-satellite networks (TSNs) can provide worldwide users with ubiquitous and seamless network services. Meanwhile, malicious eavesdropping is posing tremendous challenges on secure transmissions of TSNs due to their widescale wireless coverage. In this paper, we propose an aerial bridge scheme to establish secure tunnels for legitimate transmissions in TSNs. With the assistance of unmanned aerial vehicles (UAVs), massive transmission links in TSNs can be secured without impacts on legitimate communications. Owing to the stereo position of UAVs and the directivity of directional antennas, the constructed secure tunnel can significantly relieve confidential information leakage, resulting in the precaution of wiretapping. Moreover, we establish a theoretical model to evaluate the effectiveness of the aerial bridge scheme compared with the ground relay, non-protection, and UAV jammer schemes. Furthermore, we conduct extensive simulations to verify the accuracy of theoretical analysis and present useful insights into the practical deployment by revealing the relationship between the performance and other parameters, such as the antenna beamwidth, flight height and density of UAVs.

Height Sensitive Multi-UAV Deployment Scheme in Edge Data Acquisition System

In data acquisition scenario of edge computing, the optimization of UAV (Unmanned Aerial Vehicle) deployment is of great significance for making use of resources of UAV. We establish an optimization model of UAV cluster deployment in the edge data acquisition system. The model takes the height of UAV as the solving variable, which is more in line with the realistic characteristics. DEVIPSK-SA-FWA is proposed according to the characteristics of this model. The algorithm uses a novel coding mechanism, and uses K-Means to accelerate the convergence process of the algorithm. A variety of differential evolution mutation operators are used to form a self-adaptive strategy pool mechanism to carry out variable scale variation of population, which complete the global search well. Then fireworks algorithm searches the population locally after each round of global search. In our algorithm, global search and local search are well balanced and local optimal is effectively escaped. Finally, experimental results indicate that DEVIPSK-SA-FWA is capable of solving the model with good results, and the superiority of DEVIPSK-SA-FWA is verified through the Wilcoxon rank sum test method. In the best case, the proposed algorithm reduces energy consumption of edge data acquisition system by 32.87[Formula: see text].

Optimal Hovering Height and Power Allocation for UAV-Aided NOMA Covert Communication System

In this letter, we consider an unmanned aerial vehicle (UAV) aided covert communication system in which the UAV provides downlink transmission to the public user and covert user with non-orthogonal multiple access (NOMA). In the considered system, the covert performance can be effectively enhanced by the mobility of the UAV and the transmission from UAV to the public user. Aiming at improving the covert signal-to-noise ratio (SNR), we jointly optimize the hovering height and power allocation of UAV and formulate a signomial programming (SP) problem. To tackle the nonconvex optimization, we develop a successive geometric programming approximation (SGPA) algorithm. The optimal hovering height and power allocation are provided with numerical results and the outperformance of our design is verified.

A new connectivity model for unmanned aerial vehicle communications and flying height optimization

AbstractThis paper presents a new connectivity model for unmanned aerial vehicle (UAV) communications. We present closed‐form formulas for the probability of line‐of‐sight as a function of UAV height and distance to a ground based receiver, based on a two‐dimensional model of building and UAV locations. We show that our formulas exactly match Monte‐Carlo simulated values, whereas the existing approach over‐predicts by a factor of 2 to 3. We use the model to optimize the flying height for a UAV deployed as a mobile base station, where the goal is to maximize the number of possible connected users. We observe that the optimal height has a log‐linear characteristic. We use this to present a closed‐form formula for optimal height. We show that our techniques predict the height within 4% of realistic Monte‐Carlo simulations, and significantly outperform existing approaches which are shown to over‐predict by 40%–50%.

A Method to Study the Influence of the Pesticide Load on the Detailed Distribution Law of Downwash for Multi-Rotor UAV

Multi-rotor plant protection Unmanned Aerial Vehicles (UAVs) have suitable terrain adaptability and efficient ultra-low altitude spraying capacity, which is a significant development direction in efficient plant protection equipment. The interaction mechanisms of the wind field, droplet, and crop are unclear, and have become the bottleneck factor restricting the improvement of the deposition quality. This paper suggests a method to study the influence of the pesticide load on the detailed distribution law of downwash for a six-rotor UAV. Based on a hexahedral structured mesh, a 3D numerical calculation model was established. Analysis showed that the relative errors between the simulated and measured velocities in the z-axis were less than 11% when the downwash air flow was stable. Numerical simulations were carried out for downwash in hover under 0, 1, 2, 3, 4, and 5 kg loads. The effect of load on the airflow was evident, and the greater the load was, the higher the wind speed of downwash would be. Then, the influence of wing interference on the distribution of airflow would be more pronounced. Furthermore, under the rotation of the rotor and the extrusion of external atmospheric pressure, the “trumpet” phenomenon appeared in the downwash airflow area. As an extension, the phenomenon of the “shrinkage–expansion” was shown in the longitudinal section under heavy load, while the phenomenon of “shrinkage–expansion–shrinkage” was present under light load. After that, based on the detailed analysis of the downwash wind field, the spray height of this multi-rotor UAV was suggested to be 2.5 m or higher, and the nozzle was recommended to be mounted directly under the rotor and to have the same rotation direction as the rotor. The research in this paper lays a solid foundation for the proposal of the three-zone overlapping matching theory of wind field, droplet settlement, and canopy shaking.

Hybrid object detection methodology combining altitude-dependent local deep learning models for search and rescue operations

Due to their detection capabilities and low cost, unmanned aerial vehicles (UAVs) are commonly used in search and rescue (SAR) operations. In a SAR mission, the UAV's height may change, causing objects to shrink or increase thus affecting generalization. This paper proposes a hybrid object detection (OD) technique that combines altitude-dependent local deep learning (DL) models, each one designed for a given flight altitude range. Seven cutting-edge OD models, including YOLOv4 and v5, EfficientDet, Detectron2, MobileNet, and Faster R-CNN, were trained locally with YOLOv5 and Scaled YOLOv4 being the best performers in low and high-altitude images, respectively. The suggested hybrid strategy, which uses the best OD performers, outperformed well-known DL algorithms with 86.2% mAP on a public dataset. Computing efficiency and accuracy with images of varying resolutions were also explored. Dividing the fundamental detection issue into local subproblems that are treated separately by powerful OD networks might increase SAR capabilities.

A NOMA-Enabled Framework for Relay Deployment and Network Optimization in Double-Layer Airborne Access VANETs

A non-orthogonal multiple access (NOMA)-enabled double-layer airborne access vehicular ad hoc networks (DLAA-VANETs) architecture is designed in this paper, which consists of a high-altitude platform (HAP), multiple unmanned aerial vehicles (UAVs) and vehicles. For the designed DLAA-VANETs, we investigate the UAV deployment and network optimization problems. In particular, a UAV deployment scheme based on particle swarm optimization is presented. Then, the NOMA technique is introduced into the designed architecture, which can improve the transmission rate. Afterward, we take the information security into account and formulate a downlink total transmission rate maximization problem by optimizing UAV height and subcarrier allocation. For tackling this non-convex problem, we decouple this downlink total transmission rate maximization problem as two subproblems, where UAV height and subcarrier allocation problems are solved in turn. Moreover, the transmission performance of the designed DLAA-VANETs is analyzed, based on which the security outage probability (SOP) is derived. Finally, simulation results demonstrate that the presented UAV deployment scheme can maximize the relay coverage ratio. In addition, the proposed can achieve a higher downlink total transmission rate in comparison with the current works.

Earthwork Volume Calculation, 3D Model Generation, and Comparative Evaluation Using Vertical and High-Oblique Images Acquired by Unmanned Aerial Vehicles

In civil engineering and building construction, the earthwork volume calculation is one of the most important factors in the design and construction stages; therefore, an accurate calculation is necessary. Moreover, because managing earthworks is highly important, in this study, a three-dimensional (3D) model for earthwork calculation and management was performed using an unmanned aerial vehicle (UAV) and an RGB camera. Vertical and high-oblique images (45°, 60°, and 75°) were acquired at 50 and 100 m heights for accurate earthwork calculations and a 3D model, and data were generated by dividing the images into eight cases. Cases 1–4 were images acquired from a height of 50 m, and cases 5–8 were images acquired from a height of 100 m. (case 1: 90°, case 2: 90° + 45°, case 3: 90° + 60°, case 4: 90° + 75°, case 5: 90°, case 6: 90° + 45°, case 7: 90° + 60°, case 8: 90° + 75°). Three evaluations were performed on the data. First, the accuracy was evaluated through checkpoints for the orthophoto; second, the earthwork volumes calculated via a global positioning system and UAV were compared; finally, the 3D model was evaluated. Case 2, which showed the lowest root mean square error in the orthophoto accuracy evaluation, was the most accurate. Case 2 was the most accurate in the earthwork volume evaluation and 3D model compared to other cases. Through this study, the best results were obtained when using a vertical image and a high-oblique image of 40 to 50° when generating a 3D model for earthwork volume calculation and management. In addition, if the UAV is not affected by obstacles, it is better to shoot at about 50 m or less than to shoot the UAV height too high.

Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

Unmanned Aerial Vehicles (UAVs) will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication (URLLC) in futuristic Sixth-Generation (6G) networks. However, several security vulnerabilities and attacks have plagued previous generations of communication systems; thus, physical layer security, especially against eavesdroppers, is vital, especially for upcoming 6G networks. In this regard, UAVs have appeared as a winning candidate to mitigate security risks. In this paper, we leverage UAVs to propose two methods. The first method utilizes a UAV as Decode-and-Forward (DF) relay, whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver devices. Moreover, we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception, i.e. increasing secrecy rate, and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF relay. Additionally, simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height, blocklength, decoding error probability and transmitter-receiver separation distance. Lastly, we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

Mechanized Hybrid Rice Seed Production: Planting Density, the Flight Height of an Unmanned Aerial Vehicle, Fertilizer Application, and the Row-Ratio of Parents

The mechanized seed production of hybrid rice (Oryza sativa L.) represents significant progress in modern agriculture. However, the technologies and the crop management strategies in mechanized hybrid rice seed production are still immature. The present study was conducted with three field experiments to explore the effects of different planting densities, the flight height of an agricultural unmanned aerial vehicle (AUAV) for assisting the pollination, fertilization techniques, and the row-ratio of the restore line and the sterile line on seed yield in hybrid rice seed production. In experiment 1, three planting densities “DS1: 250000 hills per ha; DS2: 285000 hills per ha; DS3: 3,33,000 hills per ha” and three flight heights of an AUAV (FH1: above ground 2 m; FH2: above ground 3 m; FH3: above ground 4 m) were adopted. The results showed that DS1 and DS2 treatments produced a higher seed yield than the DS3 treatment, and the seed yield in the FH2 treatment was significantly higher than FH1 and FH3. In experiment 2, two fertilizer application methods, mechanized deep placement of fertilizer and traditional manual broadcasted fertilizer, were adopted. The results showed that deep placement of fertilizer significantly increased seed yield by increasing the effective panicle number and the grain number per panicle. In experiment 3, three row-ratios of sterile line and restore line at 8:1 (R1), 9:1 (R2), 10:1(R3) were adopted, and the highest seed yield was recorded in the R1 treatment.

A Tunable Caching Distribution Model for Unmanned Aerial Vehicle Networks

In existing works on performance analysis of cache-enabled unmanned aerial vehicle (UAV) networks, caching distribution is fixed, and the joint cache-level and transmission-level cooperation has not been analyzed in literature. Considering UAVs agility and line-of-sight (LOS)/ non-line-of-sight (NLOS) channel characteristics, this paper proposes a tunable caching distribution model, where content placement and transmission can be flexibly adjusted to match interference topology dynamics, and derives semi-closed expression of caching coverage probability via stochastic geometry. Specifically, UAVs will take the partition coefficient ρ to determine caching distribution, where the most popular content files are reserved in every UAV within the cooperation group and jointly transmit to the user, while other files are probabilistic stored in the remaining cache space to achieve content diversity. In addition, when requiring the less popular files, user will always connect to the UAV with the best signal-to-interference (SIR) ratio among cache hit UAVs within the cooperation group. The theoretical analysis investigates the effects of various system parameters such as UAVs height, cooperative radius, and content popularity on the caching coverage probability and optimal ρ for can be found. It can be seen that optimal ρ will be decreased firstly and then increased along with the increase of UAVs height, which reveals the tradeoff between cache hit probability and transmission reliability. Analytical results show that our proposed cache and transmission policy can achieve 34% gain of coverage probability compared to the policy of probabilistic cached.

Improved genetic algorithm based 3-D deployment of UAVs

Unmanned aerial vehicles (UAVs) are widely used as aerial base stations (BSs) to provide flexible connectivity and coverage for ground users in various scenarios such as disaster relief, traffic offloading, and so on. Especially, UAV deployment is an important issue that directly affects the coverage performance of the UAV network. In this paper, we propose a novel heuristic algorithm based three-dimensional (3-D) UAV deployment scheme while guaranteeing the connectivity of the UAV network in both static and dynamic user scenarios. For the static user scenario, we aim to deploy the minimum number of UAVs to provide coverage for the users from the perspective of deployment cost. To reduce the deployment complexity, we decouple the 3-D UAV deployment problem from the vertical and horizontal dimensions. Specifically, we firstly determine the optimal vertical height of UAVs based on the air-to-ground (A2G) model. Then, to alleviate the premature convergence of standard genetic algorithm (SGA), we design an improved genetic algorithm (IGA) to obtain the optimal horizontal locations of UAVs. On this basis, when the users move or increase, i.e., the dynamic user scenario, the already deployed UAVs cannot provide effective coverage. For this scenario, we propose a UAV redeployment scheme to maximize the number of covered users without increasing the number of UAVs. To further reduce the cost of redeployment, we firstly modify the proposed IGA to obtain a feasible set of two-dimensional (2-D) redeployed locations of the UAVs. Then, we design a backtracking algorithm (BA) based UAV movement strategy to minimize the total flying distance of the UAVs. The simulation results show that the effectiveness and convergence of our proposed schemes.

REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association

Unmanned Aerial Vehicles (UAVs) are emerging as important users of next-generation cellular networks. By operating in the sky, UAV users experience very different radio conditions than terrestrial users, due to factors such as strong Line-of-Sight (LoS) channels (and interference) and Base Station (BS) antenna misalignment. As a consequence, the UAVs may experience significant degradation to their received quality of service, particularly when they are moving and are subject to frequent handovers. The solution is to allow the UAV to be aware of its surrounding environment, and intelligently connect into the cellular network taking advantage of this awareness. In this paper we present REgression and deep Q-learning for Intelligent UAV cellular user to Base station Association (REQIBA), a solution that allows a UAV flying over an urban area to intelligently connect to underlying BSs, using information about the received signal powers, the BS locations, and the surrounding building topology. We demonstrate how REQIBA can as much as double the total UAV throughput, when compared to heuristic association schemes similar to those commonly used by terrestrial users. We also evaluate how environmental factors such as UAV height, building density, and throughput loss due to handovers impact the performance of our solution.

Downlink Performance Analysis in MIMO UAV-Cellular Communication With LOS/NLOS Propagation Under 3D Beamforming

Integrating unmanned aerial vehicles (UAVs) as the base station is a recent progress and a promising solution to assist cellular networks to improve coverage. In this paper, an analytical framework is proposed to analyze coverage probability and capacity, using stochastic geometry. We incorporate the air-to-ground (A2G), and two-piece path loss model that undergoes millimeter wave (mmWave) channel fading in both line-of-site (LOS) and non-line-of-site (NLOS). Furthermore, we assume that all users’ equipment’s (UEs) are clustered around Terrestrial Base Stations (TBS) and UAVs, according to Poisson Cluster Process (PCP), i.e., Matern cluster process. We also propose Multiple-Input-Multiple-Output (MIMO) transmission where multiple single-antenna UAVs simultaneously communicate with TBS. Initially, we obtain expressions for association probability with each tier. After that, we derive downlink coverage expression based on signal-to-interference-plus-noise-ratio (SINR), by assuming 3D directional beamforming with UAV height being not fixed. Numerical results demonstrate the efficiency and accuracy of the proposed approach.

Object Depth Measurement and Filtering from Monocular Images for Unmanned Aerial Vehicles

The flight safety of low-altitude small fixed-wing unmanned aerial vehicles (UAVs) is often threatened by obstacles such as buildings. This requires UAVs to have the ability to autonomously measure the depth of objects ahead. However, existing depth measurement methods based on multiview geometry and handcrafted features still have problems in accuracy and scene suitability. This paper proposes an object depth measurement and filtering method for UAVs by using monocular images. Firstly, the length of the line segment between feature points instead of the pixel position of feature point is used to solve object depth, which reduces the adverse effect of feature matching error. Meanwhile, in order to adapt to UAV platforms, height and attitude changes are both considered in the modeling process. Moreover, the sequence of object depth values corresponding to the image sequence is filtered by an extended Kalman filter to reduce oscillations. The effectiveness of the whole scheme is verified by visual simulation. Results show that the proposed method achieves better accuracy than other depth measurement methods based on multiview geometry.

Performance Analysis of UAV-Based Mixed RF-UWOC Transmission Systems

In this paper, we investigate the performance of a mixed radio-frequency-underwater wireless optical communication (RF-UWOC) system where an unmanned aerial vehicle (UAV), as a low-altitude mobile aerial base station, transmits information to an autonomous underwater vehicle (AUV) through a fixed-gain amplify-and-forward (AF) or decode-and-forward (DF) relay. The analysis accounts for the main factors that affect the system performance, such as the UAV height, air bubbles, temperature gradient, water salinity variations, detection techniques, and pointing errors. Employing the fixed-gain AF and DF relays, expressions for some key performance metrics are derived, e.g., outage probability (OP), average bit error rate (ABER), and average channel capacity. Moreover, in order to get further insights, asymptotic analyses for the OP and ABER are also carried out. Additionally, for the two relaying systems, we derive analytical expressions for the optimal UAV altitude that minimizes the OP. Simulation results show that the UAV altitude influences the system performance and there is an optimal altitude which ensures a minimum OP. Furthermore, it is demonstrated that the diversity order of the fixed-gain AF relaying depends on the RF link and pointing errors, while the diversity order of the DF relaying depends on the detection techniques and pointing errors.

Content Delivery Analysis in Cellular Networks With Aerial Caching and mmWAVE Backhaul

In this paper, we investigate the successful content delivery (SCD) performance in the unmanned aerial vehicle (UAV) integrated terrestrial cellular networks, where the caching-enabled UAVs are dispatched to offload the burst traffic from the cellular networks. Specifically, the UAV and terrestrial cellular network share the same spectrum resources for user downlink communications and each UAV uses millimeter wave (mmWave) communications for self-backhaul. We derive a closed-form expression of the achievable rate of the mmWave wireless backhaul link and then analyze the minimum cache hit probability to achieve a certain backhaul rate requirement. By approximating the general probabilistic line-of-sight (LoS) propagation model as a LoS ball model, we analyze the conditional SCD probabilities by leveraging stochastic geometry tools. Simulation results demonstrate that the UAV integrated cellular network can not only provide more access opportunities but also achieve higher SCD performance than the conventional terrestrial network for ground users. Moreover, there exists an optimal UAV density and height to maximize the SCD performance. Our results provide useful guidelines for the design and deployment of future UAV-assisted networks.

The Performance Analysis of Spectrum Sharing Between UAV Enabled Wireless Mesh Networks and Ground Networks

Unmanned aerial vehicle (UAV) has the advantages of large coverage and flexibility, which could be applied in disaster management to provide wireless services to the rescuers and victims. When UAVs forms an aerial mesh network, line-of-sight (LoS) air-to-air (A2A) communications have long transmission distance, which extends the coverage of multiple UAVs. However, the capacity of UAV is constrained due to the multiple hop transmissions in aerial mesh networks. In this paper, spectrum sharing between UAV enabled wireless mesh networks and ground networks is studied to improve the capacity of UAV networks. Considering two-dimensional (2D) and three-dimensional (3D) homogeneous Poisson point process (PPP) modeling for the distribution of UAVs within a vertical range $\Delta \textit h$ , stochastic geometry is applied to analyze the impact of the height of UAVs, the transmit power of UAVs, the density of UAVs and the vertical range, etc., on the coverage probability of ground network user and UAV network user. Besides, performance improvement of spectrum sharing with directional antenna is verified. With the object function of maximizing the transmission capacity, the optimal altitude of UAVs is obtained. This paper provides a theoretical guideline for the spectrum sharing of UAV enabled wireless mesh networks, which may contribute significant value to the study of spectrum sharing mechanisms for UAV enabled wireless mesh networks.