Unmanned Aerial Vehicle Communication Systems Research Articles

A Trust Based Scheme to Protect 5G UAV Communication Networks

With the increasing demands of social services, Unmanned Aerial Vehicles (UAVs)-assisted networks promote promising prospect for improving social services. The sensing data can be collected by UAVs, a large number of applications based on UAVs can be realized in 5G networks. However, the malicious UAVs may provide false information and destroy services. The 5G UAV communication systems face the security threats. Therefore, this paper develops a novel trust-based security scheme for 5G UAV communication systems. The architecture of 5G UAV communication system is first presented to improve the communication performance. Second, a trust evaluation scheme for UAVs is developed to evaluate the reliability of UAVs. By introducing the trust threshold, the malicious UAVs will be filtered out from the systems. Third, with the assistance of mobile edge computing (MEC) nodes, the detection scheme based on Q-learning technology is proposed to detect the malicious attacks. The security threats can be detected to protect the security of systems. Finally, simulation results demonstrate the effectiveness of the proposed scheme.

Joint trajectory and power optimization for securing UAV communications against active eavesdropping

Due to both of jamming and eavesdropping, active eavesdroppers can induce more serious security threats to unmanned aerial vehicle (UAV)-enabled communications. This paper considers a secure UAV communication system including both the downlink (DL) and uplink (UL) transmissions, where the confidential information is transmitted between a UAV and a ground node in the presence of an active eavesdropper. We aim to maximize the average secrecy rates of the DL and UL communications, respectively, by jointly optimizing the UAV trajectory and the UAV/ground node's transmit power control over a given flight period. Due to the non-convexity of the formulated problems, it is difficult to obtain globally optimal solutions. However, we propose efficient iterative algorithms to obtain high-quality suboptimal solutions by applying the block coordinate descent and successive convex optimization methods. Simulation results show that the joint optimization algorithms can effectively improve the secrecy rate performance for both the DL and UL communications, as compared with other baseline schemes. The proposed schemes can be considered as special cases of UAV-assisted non-orthogonal multiple access (NOMA) networks.

Secure Beamforming Scheme for Multi-Antenna UAV Communication Systems

Secure Beamforming Scheme for Multi-Antenna UAV Communication Systems

Energy-Efficient 3-D Deployment of Aerial Access Points in a UAV Communication System

In this letter, we propose an energy-efficient 3-dimensional placement of multiple aerial access points (AAPs), in the desired area, acting as flying base stations for uplink communication from a set of ground user equipment (UE). The globally optimal energy-efficient vertical position of AAPs is derived analytically by considering the inter-cell interference and AAP energy consumption. The horizontal position of AAPs which maximize the packing density of the AAP coverage area are determined using a novel regular polygon-based AAP placement algorithm. We also determine the maximum number of non-interfering AAPs that can be placed in the desired area. The effect of the AAP energy consumption on the optimal placement and the analytic findings are verified via numerical simulations.

Cache-Enabled Data Rate Maximization for Solar-Powered UAV Communication Systems

Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited to cache data from the LS and then serve GUs’ requests to handle the issue of unavailable or damaged links from the LS to the GUs. The UAV can harvest solar energy for its operation. We investigate joint cache scheduling and power allocation schemes by using the non-orthogonal multiple access (NOMA) technique to maximize the long-term downlink rate. Two scenarios for the network are taken into account. In the first, the harvested energy distribution of the GUs is assumed to be known, and we propose a partially observable Markov decision process framework such that the UAV can allocate optimal transmission power for each GU based on proper content caching over each flight period. In the second scenario where the UAV does not know the environment’s dynamics in advance, an actor-critic-based scheme is proposed to achieve a solution by learning with a dynamic environment. Afterwards, the simulation results verify the effectiveness of the proposed methods, compared to baseline approaches.

Joint Resource Allocation and 3D Aerial Trajectory Design for Video Streaming in UAV Communication Systems

Unmanned aerial vehicles (UAVs) can be flexibly deployed to offload cellular traffic or to provide video services for emergency scenarios without infrastructure. However, the inherent resource allocation and three-dimensional (3D) aerial trajectory design have not been formally studied. In this paper, we study the joint resource allocation and 3D aerial trajectory design for dynamic adaptive streaming over HTTP (DASH)-enabled services in a UAV communication system, where a UAV is employed as a base station for multiuser video streaming. Various factors are taken into account, including video data rate, quality variation, communication outage, play interruption, etc. By adopting a video streaming utility model, two fundamental problems are formulated with different practical aims: the first problem maximizes the minimum utility for all users within a given time horizon such that max-min fairness can be provided, and the second problem minimizes the UAV operation time subject to the individual utility requirement for all users to prolong UAV endurance. To tackle the first non-convex problem, we decouple it into three sub-problems, and a three-stage iterative algorithm is proposed to obtain a suboptimal solution by solving the three sub-problems with successive convex approximation and alternating optimization techniques. An exponential search based algorithm is proposed for the second problem by utilizing the structure of the considered problem and a similar three-stage iterative algorithm. Extensive simulations are carried out to evaluate the performance, and the results show that our proposed designs significantly outperform baseline schemes. Furthermore, our results reveal new insights of UAV movement for video streaming and unveil the tradeoff between utility and quality variance.

Automatic UAV Relay Communication System Based on Microwave Directional Antenna

To tackle the communication problem of unmanned aerial vehicle (UAV) complex aerial operations, we propose an automatic UAV relay communication system based on microwave directional antenna. Our system is organized by the design scheme, overall structure and working process. The system has the ability to transmit information at a distance, which solves the problem of limited communication distance caused by the transmission power limitation of UAV communication system. The system can automatically switch into different communication mode according to communication network environments to improve the communication quality. In addition, it increases the mobility and enhances endurance in severe environment to meet the emergency communication covered on demand.

Joint optimisation of UAV grouping and energy consumption in MEC‐enabled UAV communication networks

This study presents a mobile edge computing (MEC)-enabled UAV communication system, where a number of UAVs are served by terrestrial base stations (TBSs) equipped with computation resource in the non-orthogonal multiple access manner. Each UAV has to offload its computing tasks to the proper TBS due to the limited energy supply. For this, the authors aim at minimising the sum of transmission energy of UAVs and computation energy of TBSs through jointly optimising the UAV transmit power, computation resource allocation, and UAV grouping. Considering the non-convexity of this optimisation problem, they obtain the optimal solution in the coupled steps: the convex resource allocation optimisation and the combinatorial UAV grouping optimisation. By exploiting the convex nature of the resource allocation optimisation problem, they obtain the optimal transmit power and computation allocation based on the KKT conditions and the idea of gradient descent method when considering a single TBS. Then, they adopt the simulated annealing to obtain the optimal UAV grouping and TBS selection based on the proposed resource allocation optimisation algorithm. Finally, simulation results show that the proposed joint optimisation of transmit power, computation resource allocation, and UAV grouping can effectively reduce the energy consumption of MEC-aware UAV communication system.

On the Performance of RIS-Assisted Dual-Hop UAV Communication Systems

In this paper, to further improve the coverage and performance of unmanned aerial vehicle (UAV) communication systems, we propose a reconfigurable intelligent surface (RIS)-assisted UAV scheme where an RIS installed on a building is used to reflect the signals transmitted from the ground source to an UAV, and the UAV is deployed as a relay to forward the decoded signals to the destination. To model the statistical distribution of the RIS-assisted ground-to-air (G2A) links, we develop a tight approximation for the probability density function (PDF) of the instantaneous signal-to-noise ratio (SNR). By using the obtained distribution, analytical expressions for the outage probability, average bit error rate (BER), and average capacity are derived. Results show that the use of RISs can effectively improve the coverage and reliability of UAV communication systems.

A smart lightweight privacy preservation scheme for IoT-based UAV communication systems

Unmanned Aerial Vehicle (UAV) has extensively been practiced in the military and civilian surveillance systems that access sensitive data over the cellular networks. However, channel insecurity and battery limitation may not protect the aerial coverage area. Thus, sensitive information gathered through aerial vehicles causes security threats. To manage the security issues, Smart Internet of Drone (S-IoD) have been evolved to use Intelligent Personal Assistant (IPA) as a software agent while monitoring and observing areas of interest. The current state-of-the-art technologies provide ubiquitous communication to enable several Internet of Things (IoT) paradigms. It achieves a feature of a decision support system that allows the smart interaction and communication between real-time entities. IPA offers smart interaction with other smart real-time entities to gain the user’s knowledge and awareness. This paper presents an S-IoD framework for a UAV environment that independently collects sensible information. In order to reduce the computation cost of the authentication protocol, a lightweight privacy-preserving scheme (L-PPS) is introduced. The proposed L-PPS is constructive to provide the robustness between the IoT devices with a valid authentication period. To demonstrate the security and performance efficiencies, the formal verification was performed using a verification tool, Scyther, and a random oracle model. In addition, the proposed L-PPS introduces a secret token and dynamic user authentication to speed up the authentication process between the communication entities. Importantly, the authentication session of L-PPS does not use any complex cryptographic operations, whereby it has less computation and communication costs to meet the standard constraints of surveillance systems. Moreover, the obtained simulation analysis proves that the proposed L-PPS achieves better quality metrics than other authentication schemes in the literature.

Energy-Efficient Data Uploading for Cellular-Connected UAV Systems

Integrating unmanned aerial vehicles (UAVs) into cellular networks offers a promising solution to support their efficient operations and achieve high-quality communication with the ground. In this paper, we consider a cellular-connected UAV communication system, in which one energy-constrained UAV flies from a given initial location to a final location while uploading data to the ground base stations (GBSs) along its flight. We study the joint design of UAV operation time, communication scheduling, as well as UAV trajectory and transmit power to maximize the data uploading throughput, subject to the communication quality of service (QoS) requirement and UAV energy budget constraints. We first consider an offline design approach by utilizing only the channel distribution information (CDI) that is available prior to the UAV's flight, which is formulated as a non-convex optimization problem and challenging to solve. By using path disretization and successive convex approximation (SCA) techniques, an efficient alternating optimization algorithm is proposed, which can converge to a solution that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Then, we further study the online design approach by utilizing the instantaneous channel state information (CSI) that is available to the UAV in real time along its flight. As the online design problem has similar structure as that of the offline design, an adaptive online optimization algorithm is proposed. To further reduce the computational complexity, a low-complexity online algorithm based on receding horizon optimization (RHO) is developed by utilizing a combined offline and online design approach. Simulations are conducted to corroborate our study and the results demonstrate the performance gain of proposed designs as compared to various baseline schemes. Furthermore, our results unveil the tradeoff between system throughput and UAV endurance in the considered system.

Air-to-Ground Wireless Links for High-Speed UAVs

As unmanned aerial vehicles (UAVs) are becoming more popular and the demand for wireless links for UAVs is increasing, it is crucial to develop air-to-ground (A2G) wireless links for high-speed UAVs. Suffering from the high mobility and limitation of transmission power of UAVs, A2G wireless links become unstable to provide high quality communication services. In this paper, we design robust A2G wireless links for high speed UAVs, where conjunct power control is developed together with switched beamforming to maximize the power efficiency and minimize the fluctuation of A2G wireless links of millimeter wave (mmWave) signal transmission. We first present channel models for A2G wireless links of high-speed UAVs, which can be virtually seen as multiple-input multiple-output (MIMO) channels. To maximize the power efficiency, a conjunct power control problem is formulated to allocate powers for wireless links between antenna arrays on UAVs and access points (APs). For switched beamforming, beamformers are designed to provide a certain time-invariant signal-to-interference-plus-noise ratio (SINR) to minimize the SINR fluctuation of A2G wireless links. From theoretical analysis and numerical results, it is shown that the proposed architecture is able to provide robust and high quality A2G wireless links for high-speed UAV communication systems.

Learning-Based Predictive Beamforming for UAV Communications With Jittering

As a promising technique for realizing future wireless networks, unmanned aerial vehicle (UAV) communications have drawn numerous attentions. The performance of practical UAV communication systems is limited by the presence of inevitable jittering due to the inherent random wind gusts. The jittering introduces angle ambiguity which is challenging for aligning the information beams between the UAV-mounted base station (BS) and the user equipment (UE). This letter develops a learning-based predictive beamforming scheme to address the beam misalignment caused by UAV jittering. In particular, a deep learning approach is adopted to predict the angles between the UAV and the UE. By doing so, the UAV and the UE can prepare the transmit and receive beams in advance, which enables reliable UAV-based communication. Simulation results verify that the communication performance of the proposed scheme is robust to the presence of UAV jittering.

UAV communication system integrated into network traversal with mobility

In this paper, a secured unmanned aerial vehicle (UAV)-assisted heterogeneous network environment, and seamless IP prototype is proposed. UAV is controlled over the Internet to resolve a long-range communication barrier and to improve remote sensing. In the new technology, a pilot can control UAV via an end device (ED)-secured communication without any information about the network architectures, network address translation types, Internet protocol version. Network traversal with mobility (NTMobile) offers a secured communication for UAV through a public network infrastructure. NTMobile enhances the security and maintain mobility by generating keys and building tunnel using virtual IPs for two nodes inside the network. In the prototype the UAV flight controller can install a ground control station application on the UAV board. An ED can be any smart device connected to the Internet with the ability to run the remote protocols, which allows the pilot to send commands and receives data from UAV. Moreover, the pilot transmits commands through the remote desktop protocol or secure shell protocol. Experimentally, an autopilot mission is designed and uploaded to the flight controller where UAV and ED are forced to switch access network between cellular network LTE and 802.11a IEEE wireless local area network in specific waypoints. The novelty of this study is proposing secure continuous connectivity of the UAV communication and control system even during the occurrence of a network switch, which is one of the important factor in the heterogeneous network environment. The results revealed that NTMobile maintains continuous communication by re-establishing the created tunnel between UAV and ED in the proposed prototype while both are travelling in a heterogeneous network.

Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming

Thanks to the line-of-sight (LoS) transmission and flexibility, unmanned aerial vehicles (UAVs) effectively improve the throughput of wireless networks. Nevertheless, the LoS links are prone to severe deterioration by complex propagation environments, especially in urban areas. Reconfigurable intelligent surfaces (RISs), as a promising technique, can significantly improve the propagation environment and enhance communication quality by intelligently reflecting the received signals. Motivated by this, the joint UAV trajectory and RIS's passive beamforming design for a novel RIS-assisted UAV communication system is investigated to maximize the average achievable rate in this letter. To tackle the formulated non-convex problem, we divide it into two subproblems, namely, passive beamforming and trajectory optimization. We first derive a closed-form phase-shift solution for any given UAV trajectory to achieve the phase alignment of the received signals from different transmission paths. Then, with the optimal phase-shift solution, we obtain a suboptimal trajectory solution by using the successive convex approximation (SCA) method. Numerical results demonstrate that the proposed algorithm can considerably improve the average achievable rate of the system.

A Wideband Non-Stationary Air-to-Air Channel Model for UAV Communications

Unmanned aerial vehicle (UAV) communications have recently drawn great attention. To analyze and optimize the UAV communication systems, accurate and efficient UAV channel models are essential. Most existing UAV channel models are based on the assumption that both transmitter (Tx) and receiver (Rx) have fixed velocity and moving direction. However, in the realistic communication scenarios, the Tx and Rx of UAV may experience changes in both speeds and trajectories. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) is proposed for air-to-air (A2A) channels in UAV communication scenarios. A 3D Markov mobility model is used to characterize the movements of the UAV in both horizontal and vertical directions. The mobility model enables to adjust the degree of mobility randomness and covers different UAV mobility trajectories, which makes it more realistic and suitable for simulating various scenarios. In addition, some important statistical properties such as time-frequency correlation function and Doppler power spectrum are derived and analyzed. The numerical results show that the impact of vertical movement of the UAV on the time correlation function under constant-speed is larger than that of horizontal movement, however, the above phenomenon is mitigated and the non-stationarity properties of the channel are significantly affected when randomness of the mobility model is introduced. Furthermore, it is found that the movement properties of the UAV only lead to non-stationarity in the time domain. The results are useful for A2A non-stationary channel simulation and UAV communication system evaluation.

NOMA-aided UAV Communications over Correlated Rician Shadowed Fading Channels

In this paper, non-orthogonal multiple access (NOMA) is investigated as a viable solution to address spectrum scarcity in unmanned aerial vehicle (UAV) communications. Specifically, the performance analysis of a NOMA-aided UAV communication system (UCS) with dual-diversity receivers on UAVs is conducted over bivariate Rician shadowed fading channels. Using newly obtained closed-form expressions for the joint probability density function (PDF) and joint cumulative distribution function (CDF), the outage probability and finite signal-to-noise ratio (SNR) diversity gain of NOMA-aided UCS are investigated within a stochastic geometry framework. A comprehensive analysis reveals that NOMA-aided UCSs can support more UAVs on the same spectrum than OMA-based systems, with similar outage probability. It is also shown that the cross correlation affects the diversity gain of NOMA-aided and OMA-based UCSs only at low SNR regimes. Therefore, NOMA-aided UCSs can be an attractive alternative over OMA-based UCSs in future wireless systems.

NOMA-Aided UAV Data Collection System: Trajectory Optimization and Communication Design

Unmanned aerial vehicle (UAV) communication has been deemed as a promising technology to collect data for the Internet of Things (IoT) in inaccessible areas. However, due to the limited UAV flight time, traditional UAV communication may not be competent for large-scale IoT data collection. This paper considers integrating non-orthogonal multiple access (NOMA) into UAV communication systems to collect data for large-scale IoT devices within UAV flight time. We aim to minimize the total energy consumption of IoT devices while ensuring data collection, by jointly optimizing UAV trajectory, IoT device scheduling and transmit power. The formulated problem is a mixed integer non-convex problem, which is challenging to solve in general. We propose a data collection optimization algorithm (DCOA) to solve it by applying the Generalized Benders Decomposition (GBD) and successive convex approximation (SCA) techniques. Then, a greedy algorithm (GA) is also proposed to reduce complexity by simplifying the optimization of UAV trajectory and IoT device scheduling. Finally, the numerical results demonstrate that, compared with traditional UAV communication systems, the NOMA-aided UAV system performs better in terms of data collection and lower total energy consumption of IoT devices can be achieved by DCOA.

Energy Efficient 3-D UAV Control for Persistent Communication Service and Fairness: A Deep Reinforcement Learning Approach

Recently, unmanned aerial vehicles (UAVs) as flying wireless communication platform have attracted much attention. Benefiting from the mobility, UAV aerial base stations can be deployed quickly and flexibly, and can effectively establish Line-of-Sight communication links. However, there are many challenges in UAV communication system. The first challenge is energy constraint, where the UAV battery lifetime is in the order of fraction of an hour. The second challenge is that the coverage area of UAV aerial base station is limited and the commercial UAV is usually expensive. Thus, covering a large target region all the time with sufficient UAVs is quite challenging. To solve above challenges, in this paper, we propose energy efficient and fair 3-D UAV scheduling with energy replenishment, where UAVs move around to serve users and recharge timely to replenish energy. Inspired by the success of deep reinforcement learning, we propose a UAV Control policy based on Deep Deterministic Policy Gradient (UC-DDPG) to address the combination problem of 3-D mobility of multiple UAVs and energy replenishment scheduling, which ensures energy efficient and fair coverage of each user in a large region and maintains the persistent service. Simulation results reveal that UC-DDPG shows a good convergence and outperforms other scheduling algorithms in terms of data volume, energy efficiency and fairness.

Envelope Level Crossing Rate and Average Fade Duration of a Generic 3D Non-Stationary UAV Channel Model

For the unmanned aerial vehicle (UAV) communication scenarios, the time-varying fading characteristics cased by the three-dimensional(3D) scattering environment and 3D trajectory have an important impact on establishing the reliable communication link. In this paper, a generic 3D non-stationary geometry-based stochastic model (GBSM) for UAV channels is developed. Different from the traditional 3D GBSMs, the proposed model takes the 3D arbitrary trajectories of UAV into account. On this basis, two important second-order statistical properties of fading envelope, i.e., the level crossing rate (LCR) and average fading duration (AFD), are investigated and derived in details. The obtained closed-form expressions are explicit functions of flight parameters and compatible with the results in the previous works. Numerical simulations show that the simulated results are in accordance with the theoretical and measurement data under 3D flight scenarios. The proposed model and statistical properties can be applied to the optimal design of channel coding and block interleave schemes for UAV communication systems.