Multi-antenna Unmanned Aerial Vehicle Research Articles

Energy Consumption Minimization in Secure Multi-Antenna UAV-Assisted MEC Networks With Channel Uncertainty

This paper investigates the robust and secure task transmission and computation scheme in multi-antenna unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) networks, where the UAV is dual-function, i.e., aerial MEC and aerial relay. The channel uncertainty is considered during information offloading and downloading. An energy consumption minimization problem is formulated under some constraints including users’ quality of service and information security requirements and the UAV’s trajectory’s causality, by jointly optimizing the CPU frequency, the offloading time, the beamforming vectors, the artificial noise and the trajectory of the UAV, as well as the CPU frequency, the offloading time and the transmit power of each user. To solve the non-convex problem, a reformulated problem is first derived by a series of convex reformation methods, i.e., semi-definite relaxation, S-Procedure and first-order approximation, and then, solved by a proposed successive convex approximation (SCA)-based algorithm. The convergence performance and computational complexity of the proposed algorithm are analyzed. Numerical results demonstrate that the proposed scheme outperforms existing benchmark schemes. Besides, the proposed SCA-based algorithm is superior to traditional alternative optimization-based algorithm.

Outage and Throughput Analysis of UAV-Assisted NOMA Relay Systems With Indoor and Outdoor Users

Non-orthogonal multiple access (NOMA) and unmanned aerial vehicle (UAV) are two promising technologies for the fifth generation (5G) and beyond networks. On the other hand, the transition environment from outdoor to indoor is an important problem in practical wireless communication. In this paper, we mathematically study a multi-antenna UAV-assisted communication system where a multi-antenna base station (BS) communicates with indoor and outdoor users through a multiantenna UAV using the power-domain NOMA technique. The metric used to evaluate the system performance are outage probability (OP) and throughput of indoor and outdoor users under different communication urban environments. Moreover, the impacts of the UAV's altitude and location and the light-of-sight (LoS) probability on system performance are also considered. We give the exact and asymptotic closed-form OP expressions and then optimize the transmission rate to maximize the throughput of each user and the overall system throughput. Numerical results show that better system performance can be achieved by controlling the altitudes and location of the UAV, selecting an appropriate transmission rate, or equipping BS and UAV with more antennas. Monte-Carlo simulation results are provided to demonstrate the performance of the investigated system and the accuracy of the developed analytical results.

Antenna Selection and Device Grouping for Spectrum-Efficient UAV-Assisted IoT Systems

Unmanned Aerial Vehicle (UAV)-assisted Internet of Things (IoT) systems have been implemented for over a decade, from transportation to military surveillance, and is proven worthy of integration in the next generation of wireless protocols. Though UAVs have immense potential, they have major drawbacks when it comes to real-world implementation, such as energy capacity, loss of signal quality, and spectrum limitations. To overcome these challenges, integration of UAVs with spectrum-efficient techniques including cognitive radio (CR) and non-orthogonal multiple access (NOMA) has been proposed. In this paper, we incorporate transmit-antenna selection (TAS) into an underlay CRNOMA network, which provides additional benefits through employing multiple-antenna-selection approach at the UAV with the goal of better serving the ground NOMA devices. The links associated with the multi-antenna UAV are theoretically assumed to experience Nakagami-m fading distribution. We also emphasize the degraded performance caused by imperfect successive interference cancellation (SIC) when decoding signals at the ground NOMA devices. The closed-form expressions for the proposed model are derived to evaluate two main performance metrics, namely the outage probability and the ergodic capacity. Monte-Carlo simulations are performed to analyze the performance of the system in different scenarios. We observe that the power allocation factors for the devices in a group and the altitude of UAV have a noticeable impact on the performance of the system. Furthermore, the increase in the number of antennas at the UAV can complement these effects and further improve the system performance.

Placement and Resource Allocation of Wireless-Powered Multiantenna UAV for Energy-Efficient Multiuser NOMA

This paper investigates a new downlink nonorthogonal multiple access (NOMA) system, where a multiantenna unmanned aerial vehicle (UAV) is powered by wireless power transfer (WPT) and serves as the base station for multiple pairs of ground users (GUs) running NOMA in each pair. An energy efficiency (EE) maximization problem is formulated to jointly optimize the WPT time and the placement for the UAV, and the allocation of the UAV’s transmit power between different NOMA user pairs and within each pair. To efficiently solve this nonconvex problem, we decompose the problem into three subproblems using block coordinate descent. For the subproblem of intra-pair power allocation within each NOMA user pair, we construct a supermodular game with confirmed convergence to a Nash equilibrium. Given the intra-pair power allocation, successive convex approximation is applied to convexify and solve the subproblem of WPT time allocation and inter-pair power allocation between the user pairs. Finally, we solve the subproblem of UAV placement by using the Lagrange multiplier method. Simulations show that our approach can substantially outperform its alternatives that do not use NOMA and WPT techniques or that do not optimize the UAV location.

Completion time minimization for multi-antenna UAV-enabled data collection in uncorrelated Rician fading

In 5G, the unmanned aerial vehicle (UAV) is regarded as an essential way to support energy-saving, reliable, and low-cost data collection in wireless sensor networks. However, UAV-based data collection inevitably suffers from more significant data collection delays due to the UAV movement time in large application scenarios. In this paper, we consider a UAV-enabled wireless sensor network under the uncorrelated Rician fading channel, where a multi-antenna UAV is dispatched to collect data from ground sensor nodes (SNs). The objective is to minimize the mission completion time, including UAV flight and data collection time, by jointly optimizing UAV trajectory, UAV-SN transmission scheduling, and trajectory-based time allocation under the constraints of UAV speed, outage probability, data size, and transmission power. To solve this nonconvex problem, we decompose it into two subproblems: 1) trajectory optimization and 2) UAV-SN transmission scheduling and trajectory-based time allocation optimization. In the trajectory optimization, we first rewrite the outage probability constraint into the communication distance constraint and propose a Spiral-based method to find the shortest trajectory covering all SNs. Then, we propose a scheduling initialization algorithm and employ alternating optimization to solve the UAV-SN transmission scheduling and trajectory-based time allocation optimization. Finally, numerical results show that the proposed algorithm outperforms the benchmark and typical algorithms in terms of the mission completion time through a large number of experiments.

On the ergodic sum rate for multiuser satellite–aerial–terrestrial networks

In this paper, we investigate the ergodic sum rate (ESR) for the downlink of a multi-user satellite–aerial–terrestrial network (SATN) with decode-and-forward (DF) protocol, where a multi-antenna unmanned aerial vehicle (UAV) acts as an aerial relay to assist the signal convey from satellite to multiple terrestrial users, which is also corrupted by co-channel interference. To maximize the ESR of the considered system, a beamforming (BF) scheme based on statistical channel state information is proposed to conduct space division multiple access (SDMA) in the UAV–terrestrial links. Then, by assuming that the satellite–UAV link and the UAV–terrestrial links undergo correlated Shadowed-Rician fading and correlated Rayleigh fading, respectively, we derive the analytical expression of ESR for our considered system with proposed BF scheme. Finally, numerical results are provided to verify the correctness of the theoretical analysis and demonstrate the superiority of our proposed BF scheme.

Design of Hybrid Beamforming Scheme Based on Multi-Antenna Unmanned Aerial Vehicle

Design of Hybrid Beamforming Scheme Based on Multi-Antenna Unmanned Aerial Vehicle

Approaching K-Means for Multiantenna UAV Positioning in Combination With a Max-SIC-Min-Rate Framework to Enable Aerial IoT Networks

In long-range wireless communication networks, the fading channels described in channel state information are strongly related to distance and the path loss exponent and represent a major challenge in delivering the performance required to support emerging applications. Conveniently, multiple antennas and cooperative relays are efficient solutions that can combat fading channels, thereby improving networking capacity and transmission reliability. This study investigated the use of multi-antenna unmanned aerial vehicle (UAV)s as aerial Internet of Things (IoT) relays and employed their direct line-of-sight benefits to assist IoT wireless networks. To improve the outage probability, system throughput, and energy efficiency (EE), we first considered a combination of transmit antenna selection at the transmitter and the selection combining technique at the receiver to determine the best channel from the pre-coding channel matrix. Then, based on a practical model in a three-dimensional earth environment and thanks to the K-means algorithm, we investigated optimal UAV placement to obtain optimal channel state information for the non-orthogonal multiple access (NOMA)-IoT device cluster globally, thereby ensuring the quality of service for the IoT devices. We introduced a max-successive interference cancellation-min-rate framework for non-ordered NOMA devices, thus deriving theoretical expressions in novel closed forms for two independent scenarios: ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) Rayleigh and ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. By optimizing the UAV placement, the investigated results applied to the UAV scheme delivered a better performance in a NOMA-IoT network than in a terrestrial relay (TR) scheme. Finally, this study examines a variety of models and presents algorithms for Monte Carlo simulations to verify the theoretical results.

Joint Trajectory and Hybrid Beamforming Design for Multi Antenna UAV Enabled Network

In this paper, we investigate the transmission design in a multi antenna unmanned aerial vehicle (UAV)-enabled network, where the flight trajectory and hybrid digital and analog beamforming (BF) of the UAV are jointly designed, for both the fully-connected structure and sub-connected structure. Our goal is to maximize the weighted sum rate for multiply ground users, subject to the transmit power and trajectory constraints. Due to the non-convex property of the formulated problem, we propose to linearize the objective by using a newly Lagrangian dual transform. Then, an alternating optimization (AO) method is proposed, where the digital BF can be obtained by utilizing the bisection search method, while the analog BF and the flight trajectory are handled by the alternating direction of multipliers method (ADMM) algorithm. Finally, simulation results verify the performance of the proposed algorithm.

Backhaul-Aware Resource Allocation and Optimum Placement for UAV-Assisted Wireless Communication Network

Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.

Energy Efficient Beamforming Schemes for Satellite-Aerial-Terrestrial Networks

In this paper, we investigate energy efficient transmission for a satellite-aerial-terrestrial network (SATN), where a multi-antenna unmanned aerial vehicle (UAV) is employed as a relay to assist the satellite signal delivery. By considering total power constraint (TPC) or per-antenna power constraint (PPC) at the UAV, we first formulate an optimization problem to maximize the energy efficiency of the SATN, which is defined as ratio of the ergodic capacity to the total power consumption for communication at UAV. Then, by jointly exploiting array signal processing with the Dinkelbach's method, two new beamforming (BF) schemes, namely, TPC-BF and PPC-BF are proposed to solve the non-convex energy efficiency maximization problem. The main advantage of our method is that only angular information-based channel state information is used to obtain BF weight vectors so that a low implementation complexity is achieved. Furthermore, by assuming that the satellite-UAV link undergoes correlated Shadowed-Rician fading while the UAV-terminal link experiences correlated Rician fading, closed-form expressions for the statistics of the equivalent output signal-to-noise ratio are derived and, thus energy efficiency for the considered SATN with BF schemes is analytically presented. Finally, simulation results corroborate the derived expressions and confirm the effectiveness of the proposed BF schemes.

Multi-Antenna UAV Data Harvesting: Joint Trajectory and Communication Optimization

Unmanned aerial vehicle (UAV)-enabled communication is a promising technology to extend coverage and enhance throughput for traditional terrestrial wireless communication systems. In this paper, we consider a UAV-enabled wireless sensor network, where a multi-antenna UAV is dispatched to collect data from a group of sensor nodes (SNs). The objective is to maximize the minimum data collection rate from all SNs via jointly optimizing their transmission scheduling and power allocations as well as the trajectory of the UAV, subject to the practical constraints on the maximum transmit power of the SNs and the maximum speed of the UAV. The formulated optimization problem is challenging to solve as it involves non-convex constraints and discrete-value variables. To draw useful insight, we first consider the special case of the formulated problem by ignoring the UAV speed constraint and optimally solve it based on the Lagrange duality method. It is shown that for this relaxed problem, the UAV should hover above a finite number of optimal locations with different durations in general. Next, we address the general case of the formulated problem where the UAV speed constraint is considered and propose a traveling salesman problem-based trajectory initialization, where the UAV sequentially visits the locations obtained in the relaxed problem with minimum flying time. Given this initial trajectory, we then find the corresponding transmission scheduling and power allocations of the SNs and further optimize the UAV trajectory by applying the block coordinate descent and successive convex approximation techniques. Finally, numerical results are provided to illustrate the spectrum and energy efficiency gains of the proposed scheme for multi-antenna UAV data harvesting, as compared to benchmark schemes.

Performance analysis for multi-user integrated satellite and UAV cooperative networks

Satellite and unmanned aerial vehicle (UAV) communications are the two most promising technologies for providing seamless connectivity to mobile users. In this paper, we investigate the performance of a multi-antenna multi-user integrated satellite and UAV cooperative network (ISUCN). Specifically, by taking many practical parameters, such as antenna pattern and path loss into account, we first obtain the maximal output signal-to-noise ratio (SNR) expression for the ISUCN, where multi-antenna UAV is employed as an aerial relay with threshold-based amplify-and-forward (AF) protocol to assist signal transmission between satellite and multiple ground users. Then, based on the commonly used assumption that the satellite link undergoes Shadowed-Rician fading while the terrestrial links experience Nakagami-m fading, we derive an analytical expression for the outage probability (OP) of the considered network. Furthermore, the asymptotical OP expression in high SNR regime is developed to evaluate the achievable coding gain and diversity order conveniently. Finally, numerical results are given to confirm the validity of the theoretical formulas and reveal the effects of representative parameters on the system performance. Our works provide useful guidelines for the engineers in the designing ISUCNs for futuristic satellite mobile communication systems.

UAV-Aided MIMO Communications for 5G Internet of Things

The unmanned aerial vehicle (UAV) is a promising enabler of the Internet of Things (IoT) vision, due to its agile maneuverability. In this paper, we explore the potential gain of UAV-aided data collection in a generalized IoT scenario. Particularly, a composite channel model, including both large-scale and small-scale fading is used to depict typical propagation environments. Moreover, rigorous energy constraints are considered to characterize IoT devices as practically as possible. A multiantenna UAV is employed, which can communicate with a cluster of single-antenna IoT devices to form a virtual MIMO link. We formulate a whole-trajectory-oriented optimization problem, where the transmission duration and the transmit power of all devices are jointly designed to maximize the data collection efficiency for the whole flight. Different from previous studies, only the slowly varying large-scale channel state information is assumed available, to coincide with the fact that practically it is quite difficult to predictively acquire the random small-scale channel fading prior to the UAV flight. We propose an iterative scheme to overcome the nonconvexity of the formulated problem. The presented scheme can provide a significant performance gain over traditional schemes and converges quickly.

Joint 3D Beamforming and Trajectory Design for UAV-Enabled Mobile Relaying System

The goal of this paper is to investigate the security performance of the multi-antenna unmanned aerial vehicle (UAV)-enabled mobile relaying system with a multi-antenna destination in the presence of a multi-antenna eavesdropper. To improve the secrecy outage probability performance, we propose a location-based three dimensional (3D) beamforming scheme without the channel state information of the destination and the eavesdropper. To this end, we first derive the expression of the secrecy outage probability for uniform linear arrays (ULAs) and uniform circular arrays (UCAs), which is valid for arbitrary values of system parameters. The expression is practicable in the UAV-enabled mobile relaying system as the system parameters are time-variant with the movement of the UAV. Using this expression, we study the secrecy outage probability minimization problem by optimizing the 3D beamforming direction along with the trajectory of the UAV, subject to the mobility constraint and location constraint. To solve this problem, an efficient iterative algorithm is proposed. The numerical results demonstrate the effectiveness of our algorithms by comparing to other benchmark schemes, they also show the system with UCAs outperforms the system with ULAs on secrecy outage probability performance.

Energy efficient multi-antenna UAV-enabled mobile relay

In this paper, we study an energy efficient multi-antenna unmanned aerial vehicle (UAV)-enabled half-duplex mobile relaying system under Rician fading channels. By assuming that the UAV follows a circular trajectory at fixed altitude and applying the decode-and-forward relaying strategy, we maximize the energy efficiency by jointly designing beamforming, power allocation, circular radius and flight speed, subject to the sum transmit power constraint on source node and UAV relay node. First, we maximize the end-to-end signal-to-noise ratio by jointly designing beamforming and statistical power allocation. Based on the obtained beamforming and power allocation results, we then obtain a semi closed-form expression of energy efficiency, and finally maximize energy efficiency by optimizing flight speed and circular radius, allowing optimal circular radius to be obtained via numerical computation. Numerical results demonstrate that the proposed scheme can effectively enhance the system energy efficiency.

Optimal Beamforming and Performance Analysis of Wireless Relay Networks with Unmanned Aerial Vehicle

AbstractIn this paper, we investigate a wireless communication system employing a multi-antenna unmanned aerial vehicle (UAV) as the relay to improve the connectivity between the base station (BS) and the receive node (RN), where the BS–UAV link undergoes the correlated Rician fading while the UAV–RN link follows the correlated Rayleigh fading with large scale path loss. By assuming that the amplify-and-forward (AF) protocol is adopted at UAV, we first propose an optimal beamforming (BF) scheme to maximize the mutual information of the UAV-assisted dual-hop relay network, by calculating the BF weight vectors and the power allocation coefficient. Then, we derive the analytical expressions for the outage probability (OP) and the ergodic capacity (EC) of the relay network to evaluate the system performance conveniently. Finally, computer simulation results are provided to demonstrate the validity and efficiency of the proposed scheme as well as the performance analysis.

Optimization of UAV Heading for the Ground-to-Air Uplink

We consider a collection of single-antenna ground nodes communicating with a multi-antenna unmanned aerial vehicle (UAV) over a multiple-access ground-to-air communications link. The UAV uses beamforming to mitigate inter-user interference and achieve spatial division multiple access (SDMA). First, we consider a simple scenario with two static ground nodes and analytically investigate the effect of the UAV's heading on the system sum rate. We then study a more general setting with multiple mobile ground-based terminals, and develop an algorithm for dynamically adjusting the UAV heading to maximize the approximate ergodic sum rate of the uplink channel, using a prediction filter to track the positions of the mobile ground nodes. For the common scenario where a strong line-of-sight (LOS) channel exists between the ground nodes and UAV, we use an asymptotic analysis to find simplified versions of the algorithm for low and high SNR. We present simulation results that demonstrate the benefits of adapting the UAV heading in order to optimize the uplink communications performance. The simulation results also show that the simplified algorithms provide near-optimal performance.