Unmanned Aerial Vehicle Relay Networks Research Articles

Outage performance analysis of antenna selection schemes in UAV-assisted networks

In this paper, we investigate the performance of various antenna selection (AS) techniques in an unmanned aerial vehicle (UAV)-assisted relay communication system, wherein a UAV is deployed as a flying relay to establish and sustain a communication link between source and destination nodes. The AS schemes under study encompass transmit antenna selection/maximal ratio combining (TAS/MRC), joint transmit and receive antenna selection (JTRAS), and maximum ratio transmission/receive antenna selection (MRT/RAS). We present a unified outage probability (OP) performance analysis of AS techniques in UAV relay networks. We initially derive a closed-form expression for the OP under Nakagami-m fading channels. Subsequently, an asymptotic expression elucidating the array and diversity gain is derived to offer deeper insights into the performance of the studied system. Finally, Monte Carlo simulations are conducted to validate the theoretical results.

Resource Allocation of Multiple Base Stations for Throughput Enhancement in UAV Relay Networks

An unmanned aerial vehicle (UAV), with the advantages of mobility and easy deployment, serves as a relay node in wireless networks, which are known as UAV relay networks (URNs), to support user equipment that is out of service range (Uo) or does not have a direct communication link from/to the base station (BS) due to severe blockage. Furthermore, URNs have become crucial for delivering temporary communication services in emergency states or in disaster areas where the infrastructure is destroyed. The literature has explored single transmissions from one BS to a UAV to establish a wireless backhaul link in the URN; however, there exists a possibility of Uo outages due to severe interference from an adjacent BS, causing an overall throughput degradation of user equipment (UE) in the URN. In this paper, to improve the signal-to-interference-plus-noise ratio (SINR) of a wireless backhaul link, avoid an outage of Uo, and guarantee a reliable relay transmission, simultaneous transmissions from multiple BSs (e.g., macrocell BSs (mBSs) and small cell BSs (sBSs)) is considered. An outage probability is analyzed, and an optimal transmit time allocation algorithm is proposed to maximize the throughput of the UE and guarantee a reliable relay transmission. Simulation results demonstrate that simultaneous transmissions from multiple BSs in the URN leads to higher throughput and reliable transmission without an Uo outage compared to a single transmission in the URN from a single BS (e.g., mBS or sBS), and the optimization of transmit time allocation is essential in the URN.

Secrecy Outage Probability for Two-Way Integrated Satellite Unmanned Aerial Vehicle Relay Networks with Hardware Impairments

In this paper, we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments. Particularly, the closed-form expression for the secrecy outage probability is obtained. Moreover, to get more information on the secrecy outage probability in a high signal-to-noise regime, the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained, which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network. Finally, Monte Carlo simulation results are provided to show the efficiency of the theoretical analysis.

Packet Routing in Dynamic Multi-Hop UAV Relay Network: A Multi-Agent Learning Approach

The multi-hop unmanned aerial vehicle (UAV) network can serve as data relays where ground users (GUs) do not have reliable direct connections to the base station (BS). Existing works mainly focus on simple dual-hop system. In this paper, we investigate the packet routing problem in a multi-hop UAV relay network to minimize the data transmission time and enhance the network throughput. However, the dynamic network topology due to UAV mobility makes the packet routing challenging since the limited communication range of each UAV leads to volatile wireless connection. Moreover, the line-of-sight communication links may cause strong interference among UAVs. Towards this end, we propose a novel multi-agent deep reinforcement learning based algorithm, named as multi-agent QMIX (MAQMIX) to: 1) design proper UAVs’ trajectories to serve the moving GUs while maintaining the network connection; 2) allocate frequency resource properly among UAVs to alleviate the impact of interference; and 3) choose a proper next hop UAV for each data packet to reduce the transmission time and probability of network congestion. The proposed MAQMIX has two novel training mechanisms, i.e., intra-UAV and inter-UAV training mechanisms, which can tackle the large action space issue and coordinate the training among UAVs in the multi-hop UAV relay network. Simulation results demonstrate that the MAQMIX outperforms baseline schemes in terms of the network congestion avoidance, throughput, and transmission time.

Optimal UAV Deployment and Resource Management in UAV Relay Networks.

UAV equipped three-dimensional (3D) wireless networks can provide a solution for the requirements of 5G communications, such as enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC). Especially, the introduction of an unmanned aerial vehicle (UAV) as a relay node can improve the connectivity, extend the terrestrial base station (BS) coverage and enhance the throughput by taking advantage of a strong air-to-ground line of sight (LOS) channel. In this paper, we consider the deployment and resource allocation of UAV relay network (URN) to maximize the throughput of user equipment (UE) within a cell, while guaranteeing a reliable transmission to UE outside the coverage of BS. To this end, we formulate joint UAV deployment and resource allocation problems, whose analytical solutions can be hardly obtained, in general. We propose a fast and practical algorithm to provide the optimal solution for the number of transmit time slots and the UAV relay location in a sequential manner. The transmit power at BS and UAV is determined in advance based on the availability of channel state information (CSI). Simulation results demonstrate that the proposed algorithms can significantly reduce the computational effort and complexity to determine the optimal UAV location and transmit time slots over an exhaustive search.

UAV-Relaying Cooperation for Internet of Everything with CRT-Based NOMA

Due to the great potential of the combination of machine learning technology and unmanned aerial vehicle (UAV) enabled wireless communications, various optimization algorithms on resource allocation have been proposed for the Internet of Things. UAVs not only can perform the missions under the extreme conditions but also enhance the overall performance of the system as an aerial relay assisting transmission in the public and civil domains, which have been received extensive attentions. However, with the limited capacity and power constraints, they are difficult to support the transmission for the big data information users. In addition, the lack of spectrum resource poses challenges to satisfy the quality of service (QoS) of mobile users in wireless networks. To contribute to these urgent problems, this article first studies the potential and effective applications of UAVs, by introducing the Chinese remainder theorem (CRT) and nonorthogonal multiple access (NOMA) technologies into UAV relay networks. Two scenarios with/without direct transmissions between the source and destination nodes are investigated, following the decomposition and reconstruction mechanisms to satisfy the big data information transmission. Considering the user fairness, we further discuss the effect of the UAV numbers to the overall system capacity. To maximize the system capacity, the designs of transmission protocol and receiver are also discussed, in various channel conditions. Finally, a low complexity and efficient two-stage power allocation scheme is established for the perspective of users and UAV relays.

Trajectory Optimization and Resource Allocation for OFDMA UAV Relay Networks

In this paper, we consider a single-cell multi-user orthogonal frequency division multiple access (OFDMA) network with one unmanned aerial vehicle (UAV), which works as an amplify-and-forward relay to improve the quality-of-service (QoS) of the user equipments (UEs) in the cell edge. Aiming to improve the throughput while guaranteeing the user fairness, we jointly optimize the communication mode, subchannel allocation, power allocation, and UAV trajectory, which is an NP-hard problem. To design the UAV trajectory and resource allocation efficiently, we first decompose the problem into three subproblems, i.e., mode selection and subchannel allocation, trajectory optimization, and power allocation, and then solve these subproblems iteratively. Simulation results show that the proposed algorithm outperforms the random algorithm and the cellular scheme.

Joint trajectory and power optimization for mobile jammer-aided secure UAV relay network

This paper investigates the achievable average secrecy rate for a mobile jammer-aided secure unmanned aerial vehicle (UAV) relaying system. Specifically, one UAV is deployed as relay to support the communications between a source node and a destination node. An additional cooperative UAV is dispatched to enhance security by transmitting an the interference signal to interfere with any suspicious eavesdropping. With the objective of enhancing secrecy against eavesdropping, an optimization problem for jointly optimizing the time scheduling, transmit power, and UAV's trajectory is formulated while considering the energy-constrained condition of rotary-wing UAV. As the corresponding optimization problem is mixed-integer non-convex, we propose an iterative algorithm to efficiently solve this optimization problem by applying successive convex optimization and block coordinate descent techniques to derive a locally optimal solution. Simulation results demonstrate the effectiveness of the proposed algorithm compared with benchmark algorithms.

Wireless-Powered Full-Duplex UAV Relay Networks Over FTR Channels

A thorough understanding of fundamental limits of wireless-powered unmanned aerial vehicle (UAV) relay networks in millimeter waves is still missing. We narrow this gap by investigating the outage performance of a UAV-assisted wireless network over fluctuating two-ray (FTR) channels. The FTR fading model is particularly appealing since well characterizes the wireless propagation in a wide range of frequencies, including those in millimeter waves. The proposed setup consists of a source-destination pair communicating with the assistance of a UAV, which is a wireless-powered relay station operating in full-duplex mode under the amplify-and-forward protocol. For the wireless energy harvesting at the UAV, wireless power transfer (WPT), simultaneous wireless information and power transfer (SWIPT), and self-recycling energy techniques are employed together. To characterize the system outage probability, we obtain an integral-form expression derived from an approximate analysis and a simple closed-form expression derived from an asymptotic analysis at the high signal-to-noise ratio (SNR) regime. Monte Carlo simulations are provided to validate the correctness of our theoretical results and provide insights on the network performance in terms of key system parameters. Interestingly, obtained results show that the FTR fading parameters corresponding to the first hop and second hop play no role on the system outage performance at high SNR. Instead, it is mainly governed by the effect of the residual self-interference at the UAV, leading to outage floors.

Optimal Power and Bandwidth Allocation for Multiuser Video Streaming in UAV Relay Networks

We all have encountered unsatisfactory video viewing experience with mobile devices in hot spot areas where a crowd of people are demanding video streaming simultaneously. One possible solution to relieve the problem is to use the unmanned aerial vehicle (UAV) as a relay to improve the quality-of-experience (QoE). In this paper, we focus on the allocation of bandwidth and transmission power for multiuser video streaming in UAV relay networks. Our goal is to maximize the total long-term QoE of users, which are determined by the freezing time and the bit rate of video. We employ the Lyapunov optimization theory to transform the original problem with long-term average form into the drift-plus-penalty problem, and propose a decentralized allocation scheme using alternative ascending clock auction to derive the optimal solution. Simulations are conducted to demonstrate the superiority of the proposed method.

A cost-efficient elastic UAV relay network construction method with guaranteed QoS

Recently, Unmanned Aerial Vehicle (UAVs) have been widely adopted to collect data in dangerous or inaccessible areas due to their unique characteristics, including on-demand deployment, flexibility, low-cost, and mobility. However, limited power supply severely restricts the transmission range of a UAV, thus the sensed data needs to be transmitted to the ground control station (GCS) with the help of multiple UAVs in a multi-hop manner. This paper firstly describes the general process of the UAV relay network deployment, and analyzes the number of relay UAVs needed by two types of straightforward static model, i.e. track-based dynamic routing model with planned path and the infrastructure-based dynamic routing model with uncertain path. Deploying the relay UAVs in a static way as current works do cannot fulfill the requirements for an ideal UAV relay network, such as high reliability, low-cost and guaranteed quality of service. Thus, we detail our prediction-based dynamic relay network deployment model, and prove that our proposal is feasible and requires less number of relay UAVs while providing higher communication quality compared with state-of-the-art methods. Based on this model, an Elastic Relay Network Construction (ERNetC) algorithm is proposed. Finally, a series of simulation experiments are conducted on OMNeT++ simulation platform to evaluate the performance of ERNetC algorithm. Simulation results show that ERNetC algorithm outperforms existing algorithms in total interruption time as well as goodput.

Adaptive Direction Control for UAV Full-Duplex Relay Networks Using Multiple Directional Antennas

We consider a UAV (Unmanned Aerial Vehicle) relay network whereby each UAV senses data and forwards it to dedicated ground stations by means of multi-hop relaying. In particular, we focus on a UAV relay network with a simple yet realistic linear topology for which we propose an adaptive direction control scheme to achieve a high throughput performance. In the proposed scheme, each UAV, equipped with multiple directional antennas, selects either the Decode-and-Forward (DF) straight relaying method or the orthogonal relaying method, for full-duplex data transfer, i.e., data is transmitted and received simultaneously on the same frequency, but at different antennas. The originality of our proposed method is to make each UAV rotate relatively to the position of its neighbouring UAVs, in order to optimize its antenna radiation direction, according to the selected relaying method. The key advantage of the proposed method is that signal direction can be controlled without the need of heavy adaptive signal processing as in conventional beamforming techniques. In order to clarify the decision parameters for selecting a relaying method, we first evaluate the throughput performance of the two-hop relay network under the severe interference conditions of UAV networks, and next, propose a procedure for selecting a multihop relaying method. Numerical experiments show that the proposed scheme enables to achieve a high throughput performance, with low computational costs.

Interference Avoidance Position Planning in Dual-Hop and Multi-Hop UAV Relay Networks

We consider unmanned aerial vehicle (UAV)-assisted wireless communication employing UAVs as relay nodes to increase the throughput between a pair of transmitter and receiver. We focus on developing effective methods to position the UAV(s) in the sky in the presence of interference in the environment, the existence of which makes the problem non-trivial and our methodology different from the current art. We study the optimal position planning, which aims to maximize the (average) signal-to-interference-ratio (SIR) of the system, in the presence of: i) one major source of interference, ii) stochastic interference. For each scenario, we first consider utilizing a single UAV in the dual-hop relay mode and determine its optimal position. Afterward, multiple UAVs in the multi-hop relay mode are considered, for which we investigate two novel problems concerned with determining the optimal number of required UAVs and developing an optimal fully distributed position alignment method. Subsequently, we propose a cost-effective method that simultaneously minimizes the number of UAVs and determines their optimal positions to guarantee a certain (average) SIR of the system. Alternatively, for a given number of UAVs, we develop a fully distributed placement algorithm along with its performance guarantee. Numerical simulations are provided to evaluate the performance of our proposed methods.

Impact of outdated antenna selection on cache-aided UAV relay networks

In this work, we analyze the effects of outdated antenna selection on cache-aided unmanned aerial vehicle (UAV) relay networks, where the UAV acts as a decode-and-forward (DF) relay. More precisely, the transmitter communicates with destination, assisted by a UAV relay equipped with a cache, which can provide ultra-reliable and low-latency services. We firstly propose two antenna selection criteria to choose the best transmit antenna among M antennas for acquiring the maximal channel gains of direct and relaying links, respectively. Then, both analytical and approximate expressions of the outage probabilities are derived for the considered networks to evaluate the impacts caused by outdated channel state information (CSI). Moreover, the experimental results verify our analysis, while showing that the concerned cache-aided UAV relay networks provide much better services of ultra-reliable and low-latency than the one without cache.

Joint Trajectory and Power Optimization for UAV Relay Networks

In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.

Method of Geometric Connected Disk Cover Problem for UAV realy network deployment

Aiming at the problem of the effective connectivity of a large number of mobile combat units in the future aeronautic swarm operation, this paper proposes an idea of using UAV(Unmanned Aerial Vehicle) to build, and studies the deployment of the network. User coverage and network connectivity are important for a relay network planning which are studied separately in traditional ways. In order to effectively combine these two factors while the network’s survivability is taken into account. Firstly, the concept of node aggregation degree is proposed. Secondly, a performance evaluation parameter for UAV relay network is proposed based on node aggregation degree, then analyzes the lack of deterministic deployment and presents one a PSO (VFA-PSO) deployment algorithm based on virtual force. Finally, compared with the existing algorithms, the validity and stability of the algorithm are verified. The experimental results show that the VFA-PSO algorithm can effectively improve the network coverage and the survivability of the network under the premise of ensuring the network connectivity, and has better deployment effect.