In this letter, a novel framework to deliver critical spread out URLLC services deploying unmanned aerial vehicles (UAVs) in an out-of-coverage area is developed. To this end, the resource optimization problem, i.e., resource blocks (RBs) and power allocation, and optimal UAV deployment strategy are studied for UAV-assisted 5G networks to jointly maximize the average sum-rate and minimize the transmit power of UAV while satisfying the URLLC requirements. To cope with the sporadic URLLC traffic problem, an efficient online URLLC traffic prediction model based on Gaussian Process Regression (GPR) is proposed which derives optimal URLLC scheduling and transmit power strategy. The formulated problem is revealed as a mixed-integer nonlinear programming (MINLP), which is solved following the introduced successive minimization algorithm. Finally, simulation results are provided to show our proposed solution approach's efficiency.
Unmanned aerial vehicles (UAVs) are expected to coexist with conventional terrestrial cellular networks and become an important component to support high rate transmissions. This paper presents an analytical framework for evaluating the throughput performance of a downlink two-tier heterogeneous network. Considering the minimum distance constraint among UAVs, Matérn hardcore point process (MHP) is utilized to model the locations of UAVs. The locations of terrestrial base stations (BSs) are modeled by Poisson point process (PPP). Tools of stochastic geometry are invoked to derive tractable expr…
This paper studies how to achieve a high and flexible coverage performance of a large-scale cellular network that enables unmanned aerial vehicles (UAVs) for non-orthogonal multiple access (NOMA) transmission to simultaneously serve multiple users. The considered cellular network consists of a tier of base stations and a tier of UAVs. Each UAV is mounted with an intelligent reflecting surface (IRS) in order to serve as an aerial IRS reflecting signals between a base station and a user in the network. All the UAVs in the network are deployed based on a newly proposed three-dimensional (3D) poin…
Unmanned aerial vehicles (UAVs) are usually dispatched as mobile sinks to assist data collection in large-scale wireless sensor networks (WSNs). However, when considering the limitations of UAV's mobility and communication capabilities in a large-scale WSN, some sensor nodes may run out of storage space as they fail to offload their data to the UAV for an extended period of time. To minimize the data loss caused by the above issue, a joint user scheduling and trajectory planning data collection strategy is proposed in this letter, which is formulated as a non-convex optimization problem. The p…
In this paper, we investigate joint vehicle association and multi-dimensional resource management in a vehicular network assisted by multi-access edge computing (MEC) and unmanned aerial vehicle (UAV). To efficiently manage the available spectrum, computing, and caching resources for the MEC-mounted base station and UAVs, a resource optimization problem is formulated and carried out at a central controller. Considering the overlong solving time of the formulated problem and the sensitive delay requirements of vehicular applications, we transform the optimization problem using reinforcement lea…
Modern day wireless networks have tremendously evolved driven by a sharp increase in user demands, continuously requesting more data and services. This puts significant strain on infrastructure based macro cellular networks due to the inefficiency in handling these traffic demands, cost effectively. A viable solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial nodes between the macro and small cell tiers for improving coverage and boosting capacity. This letter investigates the problem of user demand based UAV assignment over geographical areas subject to high traffic …
Unmanned aerial vehicle (UAV)-assisted multi-access edge computing (MEC) has become one promising solution for energy-constrained devices to meet the computation demand and the stringent delay requirement. In this work, we investigate a multiple UAVs-assisted two-stage MEC system in which the computation-intensive and delay-sensitive tasks of mobile devices (MDs) are cooperatively executed on both MEC-enabled UAVs and terrestrial base station (TBS) attached with the MEC server. Specifically, UAVs provide the computing and relaying services to the mobile devices. In this regard, we formulate a …
Propelled by multi-user MIMO (MU-MIMO) technology, unmanned aerial vehicles (UAVs) as mobile hotspots have recently emerged as an attractive wireless communication paradigm. Rate adaptation (RA) becomes indispensable to enhance UAV communication robustness against UAV mobility-induced channel variances. However, existing MU-MIMO RA algorithms are mainly designed for ground communications with relatively stable channel coherence time, which incurs channel measurement staleness and sub-optimal rate selections when coping with highly dynamic air-to-ground links. In this paper, we propose SensRate…
UAV-Assisted Joint Data Collection and Wireless Power Transfer for Batteryless Sensor Networks
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）
Resource Allocation and Sharing for UAV-Assisted Integrated TN-NTN with Multi-Connectivity
Kyung Hee University（庆熙大学）；ID Lab, Ghent University（根特大学 ID 实验室）；National University of Sciences and Technology, Balochistan Campus, Pakistan（巴基斯坦国立科学与技术大学博洛奇斯坦校区）；Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg（卢森堡大学安全、可靠性与信任跨学科中心）
In this paper, we investigate traits and trade-offs of a system combining UAVs with BS or C-RAN for extending the terrestrial wireless coverage over the sea in emergency situations. Results for an over the sea deployment link budget show the trade-off between power consumption and throughput to meet the Search and Rescue targets.
Next-generation wireless networks will deploy UAVs dynamically as aerial base stations (UAV-BSs) to boost the wireless network coverage in the out of reach areas. To provide an efficient service in stochastic environments, the optimal number of UAV-BSs, their locations, and trajectories must be specified appropriately for different scenarios. Such deployment requires an intelligent decision-making mechanism that can deal with various variables at different times. This paper proposes a multi UAV-BS deployment model for smart farming, formulated as a Multi-Criteria Decision Making (MCDM) method …
Unmanned aerial vehicles (UAVs) can provide an effective solution for improving the coverage, capacity, and the overall performance of terrestrial wireless cellular networks. In particular, UAV-assisted cellular networks can meet the stringent performance requirements of the fifth generation new radio (5G NR) applications. In this paper, the problem of energy-efficient resource allocation in UAV-assisted cellular networks is studied under the reliability and latency constraints of 5G NR applications. The framework of ruin theory is employed to allow solar-powered UAVs to capture the dynamics o…
The market size of Unmanned Aerial Vehicles (UAVs, a.k.a drones) can reach up to 10% of the global market value. In particular, drone delivery is one of the most attractive applications. The growing number of drones requires appropriate traffic management systems that will rely on cellular networks. However, it has been shown in the literature that these networks cannot provide reliable communication due to low coverage probability and frequent handovers. This article presents a potential solution targeting these problems while requiring no modifications of the existing infrastructure. Namely,…
This paper studies an unmanned aerial vehicle (UAV)-assisted wireless network, where a UAV is dispatched to gather information from ground sensor nodes (SN) and transfer the collected data to the depot. The information freshness is captured by the age of information (AoI) metric, whilst the energy consumption of the UAV is seen as another performance criterion. Most importantly, the AoI and energy efficiency are inherently competing metrics, since decreasing the AoI requires the UAV returning to the depot more frequently, leading to a higher energy consumption. To this end, we design UAV paths…
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 a major source of interference, the existence of which makes the problem non-trivial. First, we consider utilizing a single UAV, for which we develop a theoretical framework to determine its optimal position aiming to maximize the SIR of the system. To this end, we investigate the problem for three practical scenarios, in which t…
TU Dortmund University（多特蒙德工业大学）；Communication Networks Institute（通信网络研究所）
The integration of small-scale Unmanned Aerial Vehicles (UAVs) into Intelligent Transportation Systems (ITSs) will empower novel smart-city applications and services. After the unforeseen outbreak of the COVID-19 pandemic, the public demand for delivery services has multiplied. Mobile robotic systems inherently offer the potential for minimizing the amount of direct human-to-human interactions with the parcel delivery process. The proposed system-of-systems consists of various complex aspects such as assigning and distributing delivery jobs, establishing and maintaining reliable communication …
Shanghai Jiao Tong University（上海交通大学）；Zhejiang University of Technology（浙江工业大学）
This paper investigates an unmanned aerial vehicle (UAV)-assisted wireless powered mobile-edge computing (MEC) system, where the UAV powers the mobile terminals by wireless power transfer (WPT) and provides computation service for them. We aim to maximize the computation rate of terminals while ensuring fairness among them. Considering the random trajectories of mobile terminals, we propose a soft actor-critic (SAC)-based UAV trajectory planning and resource allocation (SAC-TR) algorithm, which combines off-policy and maximum entropy reinforcement learning to promote the convergence of the alg…
Fog computing is an emerging distributed computing model for the Internet of Things (IoT). It extends computing and caching functions to the edge of wireless networks. Uncrewed Aerial Vehicles (UAVs) provide adequate support for fog computing. UAVs can not only act as a relay between mobile users and physically remote edge devices to avoid costly long-range wireless communications but also are equipped with computing facilities that can take over specific tasks. In this paper, we aim to optimize the energy efficiency of a fog computing system assisted by a single UAV by planning the trajectori…
Due to the flexibility and low operational cost, dispatching unmanned aerial vehicles (UAVs) to collect information from distributed sensors is expected to be a promising solution in Internet of Things (IoT), especially for time-critical applications. How to maintain the information freshness is a challenging issue. In this paper, we investigate the fresh data collection problem in UAV-assisted IoT networks. Particularly, the UAV flies towards the sensors to collect status update packets within a given duration while maintaining a non-negative residual energy. We formulate a Markov Decision Pr…
Integrating unmanned aerial vehicles (UAV) to non-orthogonal multiple access (NOMA) visible light communications (VLC) exposes many potentials over VLC and NOMA-VLC systems. In this circumstance, user grouping is of importance to reduce the NOMA decoding complexity when the number of users is large; however, this issue has not been considered in the existing study. In this paper, we aim to maximize the weighted sum-rate of all the users by jointly optimizing UAV placement, user grouping, and power allocation in downlink NOMA-VLC systems. We first consider an efficient user clustering strategy,…
Digital Twin Enabled Simultaneous Learning and Modeling for UAV-assisted Secure Communications with Eavesdropping Attacks
School of Intelligent Systems Engineering, Sun Yat-sen University（中山大学智能系统工程学院）；Department of Equipment Management and Unmanned Aerial Vehicle Engineering, Air Force Engineering University（空军工程大学装备管理与无人机工程系）
UAV-Assisted Resilience in 6G and Beyond Network Energy Saving: A Multi-Agent DRL Approach
National Economics University（国立经济大学）；Norwegian University of Science and Technology（挪威科技大学）；Waseda University（早稻田大学）；Duy Tan University（杜维谭大学）；University of Luxembourg（卢森堡大学）；National Academy of Education Management（国家教育管理学院）
In this letter, we study the energy efficiency (EE) optimisation of unmanned aerial vehicles (UAVs) providing wireless coverage to static and mobile ground users. Recent multi-agent reinforcement learning approaches optimise the system's EE using a 2D trajectory design, neglecting interference from nearby UAV cells. We aim to maximise the system's EE by jointly optimising each UAV's 3D trajectory, number of connected users, and the energy consumed, while accounting for interference. Thus, we propose a cooperative Multi-Agent Decentralised Double Deep Q-Network (MAD-DDQN) approach. Our approach…
Unmanned aerial vehicle (UAV)-assisted data collection has been emerging as a prominent application due to its flexibility, mobility, and low operational cost. However, under the dynamic and uncertainty of IoT data collection and energy replenishment processes, optimizing the performance for UAV collectors is a very challenging task. Thus, this paper introduces a novel framework that jointly optimizes the flying speed and energy replenishment for each UAV to significantly improve the data collection performance. Specifically, we first develop a Markov decision process to help the UAV automatic…
Unmanned Aerial Vehicle (UAV) has been recognized as a promising way to assist future wireless communications due to its high flexibility of deployment and scheduling. In this paper, we focus on temporarily deployed UAVs that provide downlink data offloading in some regions under a macro base station (MBS). Since the manager of the MBS and the operators of the UAVs could be of different interest groups, we formulate the corresponding spectrum trading problem by means of contract theory, where the manager of the MBS has to design an optimal contract to maximize its own revenue. Such contract co…
Unmanned aerial vehicles (UAVs) are emerging as enablers for supporting many applications and services, such as precision agriculture, search and rescue, temporary network deployment or coverage extension, and security. UAVs are being considered for integration into emerging 5G networks as aerial users or network support nodes. We propose to leverage UAVs in 5G to assist in the prevention, detection, and recovery of attacks on 5G networks. Specifically, we consider jamming, spoofing, eavesdropping and the corresponding mitigation mechanisms that are enabled by the versatility of UAVs. We intro…
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption. In the considered scenario, a UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users. Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the D…
Recently, Unmanned Aerial Vehicle (UAV) based communications systems have attracted increasing research and commercial interest due to their cost effective deployment and ease of mobility.During natural disasters and emergencies, such networks are extremely useful to provide communication service. In such scenarios, UAVs position and trajectory must be optimal to maintain Quality of Service at the user end. This paper focuses on the deployment of an SDN-based UAV network providing communication service to the users. We consider the deployment of the system in stadiums and events. In this paper…
National University of Defense Technology（国防科技大学）；KU Leuven（鲁汶大学）；Delft University of Technology（代尔夫特理工大学）
Autonomous flight for UAVs relies on visual information for avoiding obstacles and ensuring a safe collision-free flight. In addition to visual clues, safe UAVs often need connectivity with the ground station. In this paper, we study the synergies between vision and communications for edge computing-enabled UAV flight. By proposing a framework of Edge Computing Assisted Autonomous Flight (ECAAF), we illustrate that vision and communications can interact with and assist each other with the aid of edge computing and offloading, and further speed up the UAV mission completion. ECAAF consists of t…
Motivated by the need to ensure timely delivery of information (e.g., status updates) in the Internet-of-things (IoT) paradigm, this paper investigates the role of an Unmanned aerial vehicle (UAV) as a mobile relay to minimize the average Peak Age-of-information (PAoI) for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytic…
The communication energy in a wireless network of mobile autonomous agents should be defined to include the propulsion energy as well as the transmission energy used to facilitate information transfer. We therefore develop communicationtheoretic and Newtonian dynamic models of the communication and locomotion expenditures of an unmanned aerial vehicle (UAV). These models are used to formulate a novel nonlinear optimal control problem (OCP) for arbitrary networks of autonomous agents. This is the first work to consider mobility as a decision variable in UAV networks with multiple access channel…
