Journal articles: 'UAV-aided Wireless Networks'

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Teng, Sihao. "UAV Assisted Wireless Network." Journal of Physics: Conference Series 2078, no. 1 (November 1, 2021): 012022. http://dx.doi.org/10.1088/1742-6596/2078/1/012022.

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Abstract With the increasing demand of social network service, the unmanned aerial vehicle has been used as a base station to assist terrestrial base station to improve wireless network performance. UAV base station provides high efficiency and wider data transmitting range due to the small size and flexibility of UAV. However, UAV wireless network faces few challenges. Energy efficiency is hard to achieve due to small battery capacity. The base station performance is also very important. It can be determined by aircraft’s flying stability, the performance of air to ground communication and the limitation of wireless coverage of UAV. In order to achieve optimal UAV deployment, improving deployment delay, communication coverage and UAV number limitation are important. Trajectory optimizing problems also need to be considered. This article analyzes UAV assisted wireless networks through investigating UAV energy efficiency, UAV aided network performance, optimal deployment methods and flight trajectory. It is shown that energy efficiency can be optimized by applying LoS based channel in UAV trajectory planning. And inequality iteration algorithm proposed by former researchers is used to determine optimal flight trajectory. This method is efficient because of cellular network’s interference-free ability. As for performance, channel selection methods are used to reduce overflow rate and boost data-received size. These methods are analyzed and proved to be effective for improving UAV aided wireless network performance.

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Arafat, Muhammad Yeasir, Md Arafat Habib, and Sangman Moh. "Routing Protocols for UAV-Aided Wireless Sensor Networks." Applied Sciences 10, no. 12 (June 12, 2020): 4077. http://dx.doi.org/10.3390/app10124077.

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Recently, unmanned aerial vehicles (UAVs) attracted significant popularity in both military and civilian domains for various applications and services. Moreover, UAV-aided wireless sensor networks (UAWSNs) became one of the interesting hot research topics. This is mainly because UAWSNs can significantly increase the network coverage and energy utilization compared to traditional wireless sensor networks (WSNs). However, the high mobility, dynamic path, and variable altitude of UAVs can cause not only unforeseen changes in the network topology but also connectivity and coverage problems, which can affect the routing performance of the network. Therefore, the design of a routing protocol for UAWSNs is a critical task. In this paper, the routing protocols for UAWSNs are extensively investigated and discussed. Firstly, we classify the existing routing protocols based on different network criteria. They are extensively reviewed and compared with each other in terms of advantages and limitation, routing metrics and policies, characteristics, difference performance factors, and different performance optimization factors. Furthermore, open research issues and challenges are summarized and discussed.

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Iakovlev, Roman, and Anton Saveliev. "Approach to implementation of local navigation of mobile robotic systems in agriculture with the aid of radio modules." Telfor Journal 12, no. 2 (2020): 92–97. http://dx.doi.org/10.5937/telfor2002092i.

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In this paper an approach is presented, enabling to solve the problem of local navigation of mobile robotic platforms (MRP), based on utilization of wireless networks with mesh topology. Establishment of wireless networks was ensured, based on the set of radio modules, mounted on unmanned aerial vehicles (UAV), comprising a swarm. This paper presents a developed algorithm for establishment of such wireless networks, aided by LoRa-technology, as well as an algorithm for MRP localization, based on analysis of signal level, where the incoming signals are fed from MRP group radio modules to radio modules of wireless data transfer network. An algorithmic model is given for task distribution among UAV and to implement navigational capabilities of MRP swarm. In some experiments descending dependencies of absolute error value, pertinent to MRP, from the number of UAV in action were revealed, as well as of averaged deflection value of MRP positions in motion along their paths from the number of UAV in action. Thereby the averaged value of MRP localization error, depending on the number of UAV in action, was from 8.14 to 17.13 m, and the averaged value of MRP position deflection - from 16.38 to 57.12 m, respectively.

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Hua, Meng, Yi Wang, Zhengming Zhang, Chunguo Li, Yongming Huang, and Luxi Yang. "Power-Efficient Communication in UAV-Aided Wireless Sensor Networks." IEEE Communications Letters 22, no. 6 (June 2018): 1264–67. http://dx.doi.org/10.1109/lcomm.2018.2822700.

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Hua, Meng, Yi Wang, Zhengming Zhang, Chunguo Li, Yongming Huang, and Luxi Yang. "Energy-efficient optimisation for UAV-aided wireless sensor networks." IET Communications 13, no. 8 (May 14, 2019): 972–80. http://dx.doi.org/10.1049/iet-com.2018.5441.

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Liu, Bin, and Hongbo Zhu. "Energy-Effective Data Gathering for UAV-Aided Wireless Sensor Networks." Sensors 19, no. 11 (May 31, 2019): 2506. http://dx.doi.org/10.3390/s19112506.

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Unmanned aerial vehicles (UAVs) are capable of serving as a data collector for wireless sensor networks (WSNs). In this paper, we investigate an energy-effective data gathering approach in UAV-aided WSNs, where each sensor node (SN) dynamically chooses the transmission modes, i.e., (1) waiting, (2) conventional sink node transmission, (3) uploading to UAV, to transmit sensory data within a given time. By jointly considering the SN’s transmission policy and UAV trajectory optimization, we aim to minimize the transmission energy consumption of the SNs and ensure all sensory data completed collected within the given time. We take a two-step iterative approach and decouple the SN’s transmission design and UAV trajectory optimization process. First, we design the optimal SNs transmission mode policy with preplanned UAV trajectory. A dynamic programming (DP) algorithm is proposed to obtain the optimal transmission policy. Then, with the fixed transmission policy, we optimize the UAV’s trajectory from the preplanned trace with recursive random search (RRS) algorithm. Numerical results show that the proposed scheme achieves significant energy savings gain over the benchmark schemes.

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Berrahal, Sarra, Jong-Hoon Kim, Slim Rekhis, Noureddine Boudriga, Deon Wilkins, and Jaime Acevedo. "Border surveillance monitoring using Quadcopter UAV-Aided Wireless Sensor Networks." Journal of Communications Software and Systems 12, no. 1 (March 22, 2016): 67. http://dx.doi.org/10.24138/jcomss.v12i1.92.

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In this paper we propose a novel cooperative bordersurveillance solution, composed of a Wireless Sensor Network (WSN) deployed terrestrially to detect and track trespassers, and a set of lightweight unmanned aircraft vehicles (UAVs) in the form of quadcopters that interact with the deployed WSN to improve the border surveillance, the detection and investigation of network failures, the maintenance of the sensor network, the tracking of trespasser, the capture and transmission of realtime video of the intrusion scene, and the response to hostage situations. A heuristic-based scheduling algorithm is described to optimize the tracking mission by increasing the rate of detected trespassers spotted by the quadcopters. Together with the design of the electrical, mechanical and software architecture of the proposed VTail quadcopter, we develop in this paper powerless techniques to accurately localize terrestrial sensors using RFID technology, compute the optimal positions of the new sensors to drop, relay data between isolated islands of nodes, and wake up sensors to track intruders. The developed VTail prototype is tested to provide valid and accurate parameters’ values to the simulation. The latter is conducted to evaluate the performance of the proposed WSN-based surveillance solution.

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Shi, Baihua, Yang Wang, Danqi Li, Wenlong Cai, Jinyong Lin, Shuo Zhang, Weiping Shi, Shihao Yan , and Feng Shu. "STAR-RIS-UAV-Aided Coordinated Multipoint Cellular System for Multi-User Networks." Drones 7, no. 6 (June 17, 2023): 403. http://dx.doi.org/10.3390/drones7060403.

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Different from conventional reconfigurable intelligent surfaces (RIS), simultaneous transmitting and reflecting RIS (STAR-RIS) can reflect and transmit signals to the receiver. In this paper, to serve more ground users and increase deployment flexibility, we investigate an unmanned aerial vehicle (UAV) equipped with STAR-RIS (STAR-RIS-UAV)-aided wireless communications for multi-user networks. Energy splitting (ES) and mode switching (MS) protocols are considered to control the reflection and transmission coefficients of STAR-RIS elements. To maximize the sum rate of the STAR-RIS-UAV-aided coordinated multipoint (CoMP) cellular system for multi-user networks, the corresponding beamforming vectors as well as transmitted and reflected coefficient matrices are optimized. Specifically, instead of adopting the alternating optimization, we design an iteration method to optimize all variables for both the ES and MS protocols at the same time. Simulation results reveal that the STAR-RIS-UAV-aided CoMP system has a much higher sum rate than systems with conventional RIS or without RIS. Furthermore, the proposed structure is more flexible than fixed STAR-RIS and could greatly promote the sum rate.

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Cao, Dongju, Wendong Yang, and Gangyi Xu. "Joint Trajectory and Communication Design for Buffer-Aided Multi-UAV Relaying Networks." Applied Sciences 9, no. 24 (December 15, 2019): 5524. http://dx.doi.org/10.3390/app9245524.

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With the rapid development and evolvement of unmanned aerial vehicle (UAV) technology, UAV aided wireless communication technology has been widely studied recently. In this paper, a buffer aided multi-UAV relaying network is investigated to assist blocked ground communication. According to the mobility and implementation flexibility of UAV relays, it is assumed that the communication link between air-to-ground is the Rician fading channel. On the basis of information causality, we derive the state change of the information in the buffer of UAV relays and maximize the end-to-end average throughput by join the relay selection, UAV transmit power, and UAV trajectory optimization. However, the considered problem is a mixed integer non-convex optimization problem, and therefore, it is difficult to solve directly with general optimization methods. In order to make the problem tractable, an efficient iterative algorithm based on the block coordinate descent and the successive convex optimization techniques is proposed. The convergence of the proposed algorithm will be verified analytically at the end of this paper. The simulation results show that by alternately optimizing the relay selection, UAV transmit power, and UAV trajectory, the proposed algorithm is able to achieve convergence quickly and significantly improve the average throughput, as compared to other benchmark schemes.

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Castellanos, German, Margot Deruyck, Luc Martens, and Wout Joseph. "Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks." Sensors 19, no. 15 (July 30, 2019): 3342. http://dx.doi.org/10.3390/s19153342.

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Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users—access network—and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul networks; however, full coverage was difficult to achieve. Finally, we discuss the influence of the flight height and the number of requesting users concerning the network performance and propose an optimal configuration and new mechanisms to improve the network capacity, based on realistic restrictions.

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Sun, Yanzan, Xinlin Zhong, Fan Wu, Xiaojing Chen, Shunqing Zhang, and Nan Dong. "Multi-UAV Content Caching Strategy and Cooperative, Complementary Content Transmission Based on Coalition Formation Game." Sensors 22, no. 9 (April 19, 2022): 3123. http://dx.doi.org/10.3390/s22093123.

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The transmission of a large amount of video and picture content brings more challenges to wireless communication networks. Unmanned aerial vehicle (UAV)-aided small cells with active content caching deployed on cellular networks are recognized as a promising way to alleviate wireless backhaul and support flexible coverage. However, a UAV cannot operate for a long time due to limited battery life, and its caching capacity is also limited. For this, a multi-UAV content-caching strategy and cooperative, complementary content transmission among UAVs are jointly studied in this paper. Firstly, a user-clustering-based caching strategy is designed, where user clustering is based on user similarity, concurrently taking into consideration similarities in content preference and location. Then, cooperative, complementary content transmission between multiple UAVs is modeled as a coalition formation game (CFG) to maximize the utility of the whole network. Finally, the effectiveness of the proposed algorithms is demonstrated through numerical simulations.

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Quan, Xiaoya. "QoS-Aware Power Allocation for Multi-UAV Aided Networks." Journal of Physics: Conference Series 2113, no. 1 (November 1, 2021): 012012. http://dx.doi.org/10.1088/1742-6596/2113/1/012012.

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Abstract UAV base stations (UAVBS’s) have been proposed as a revolution for the new architecture of 5G networks. The UAVBS’s can be deployed as access points to provide wireless services to users in emergency scenarios. However, it is challenging to solve the highly coupled problem for UAVBS deployment and power allocation. In the meanwhile, the hybrid analog and digital beamforming is leverage to reduce the hardware cost for beamforming in 5G networks. In this work, we first use k-means algorithm to solve the 3D placement of UAVBS’s by exploiting the optimal coverage altitude. Next, power allocation problem is resolved using the difference-of-two-convex functions (D.C.) programming algorithm. Furthermore, the quality of service (QoS) for each user is guaranteed by adjusting the transmitted power. Finally, extensive experiments are conducted to demonstrate the feasibility of the proposed algorithm.

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Mignardi, Silvia, Riccardo Marini, Roberto Verdone, and Chiara Buratti. "On the Performance of a UAV-Aided Wireless Network Based on NB-IoT." Drones 5, no. 3 (September 9, 2021): 94. http://dx.doi.org/10.3390/drones5030094.

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In recent years, interest in Unmanned Aerial Vehicles (UAVs) as a means to provide wireless connectivity has substantially increased thanks to their easy, fast and flexible deployment. Among the several possible applications of UAV networks explored by the current literature, they can be efficiently employed to collect Internet-of-Things (IoT) data because the non-stringent latency and small-size traffic type is particularly suited for UAVs’ inherent characteristics. However, the implications coming from the implementation of existing technology in such kinds of nodes are not straightforward. In this article, we consider a Narrow Band IoT (NB-IoT) network served by a UAV base station. Because of the many configurations possible within the NB-IoT standard, such as the access structure and numerology, we thoroughly review the technical aspects that have to be implemented and may be affected by the proposed UAV-aided IoT network. For proper remarks, we investigate the network performance jointly in terms of the number of successful transmissions, access rate, latency, throughput and energy consumption. Then, we compare the obtained results on different and known trajectories in the research community and study the impact of varying UAV parameters such as speed and height. Moreover, the numerical assessment allows us to extend the discussion to the potential implications of this model in different scenarios. Thus, this article summarizes all the main aspects that must be considered in planning NB-IoT networks with UAVs.

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Cao, Dongju, Wendong Yang, and Ning Li. "Throughput enhancement of buffer-aided multi-hop UAV relaying wireless networks." AEU - International Journal of Electronics and Communications 131 (March 2021): 153596. http://dx.doi.org/10.1016/j.aeue.2020.153596.

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Ebrahimi, Dariush, Sanaa Sharafeddine, Pin-Han Ho, and Chadi Assi. "UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks." IEEE Internet of Things Journal 6, no. 2 (April 2019): 1893–905. http://dx.doi.org/10.1109/jiot.2018.2878834.

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Esrafilian, Omid, Rajeev Gangula, and David Gesbert. "Learning to Communicate in UAV-Aided Wireless Networks: Map-Based Approaches." IEEE Internet of Things Journal 6, no. 2 (April 2019): 1791–802. http://dx.doi.org/10.1109/jiot.2018.2879682.

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Di, Xiaofei, and Yang Chen. "Joint Position and Time Allocation Optimization of UAV-Aided Wireless Powered Relay Communication Systems." Wireless Communications and Mobile Computing 2021 (April 17, 2021): 1–10. http://dx.doi.org/10.1155/2021/5537517.

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The Internet of things (IoT) has emerged as a platform for connecting massive physical devices to collect and analyze data for decision-making. Wireless devices in IoT are usually energy-constrained and thus need to be powered by a stable and reliable energy source in order to maintain a long network lifetime. An unmanned aerial vehicle (UAV) as an energy source is a proper and applicable way to supply energy to wireless devices in IoT, due to its flexibility and potential of providing line-of-sight (LOS) links for wireless air-to-ground channels. In this paper, a UAV-aided wireless powered relay communication system is presented, where a UAV firstly emits energy to a source and a relay, and then, the source and relay cooperatively transmit information to their destination. To explore the performance limit of the system, a problem is formulated by jointly optimizing the position of the UAV and time allocation to maximize the achievable information rate of the system. By deriving the explicit expressions of the optimal position of UAV and optimal time fraction, the nonconvex optimization problem is efficiently solved. Simulation results show that our proposed method significantly outperforms the benchmark methods.

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Li, Jun, Rahim Kacimi, Tianyi Liu, Xiaoyan Ma, and Riadh Dhaou. "Non-Terrestrial Networks-Enabled Internet of Things: UAV-Centric Architectures, Applications, and Open Issues." Drones 6, no. 4 (April 10, 2022): 95. http://dx.doi.org/10.3390/drones6040095.

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Although Unmanned Aerial Vehicles (UAVs)-aided wireless sensor networks (WSNs) have gained many applications, it is not for long that research works have been produced to define effective algorithms and protocols. In this article, we address the UAV-enabled WSN (U-WSN), explore the performance and the capability of the UAV, define the UAV functionalities as a communication node, and describe the architectures and the relevant typical technologies that emerge from this new paradigm. Furthermore, this article also identifies the main factors which influence the U-WSN design and analyzes the open issues and challenges in U-WSN. These insights may serve as motivations and guidelines for future designs of UAV-enabled WSNs.

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Rafiq, Ahsan, Reem Alkanhel, Mohammed Saleh Ali Muthanna, Evgeny Mokrov, Ahmed Aziz, and Ammar Muthanna. "Intelligent Resource Allocation Using an Artificial Ecosystem Optimizer with Deep Learning on UAV Networks." Drones 7, no. 10 (October 3, 2023): 619. http://dx.doi.org/10.3390/drones7100619.

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An Unmanned Aerial Vehicle (UAV)-based cellular network over a millimeter wave (mmWave) frequency band addresses the necessities of flexible coverage and high data rate in the next-generation network. But, the use of a wide range of antennas and higher propagation loss in mmWave networks results in high power utilization and UAVs are limited by low-capacity onboard batteries. To cut down the energy cost of UAV-aided mmWave networks, Energy Harvesting (EH) is a promising solution. But, it is a challenge to sustain strong connectivity in UAV-based terrestrial cellular networks due to the random nature of renewable energy. With this motivation, this article introduces an intelligent resource allocation using an artificial ecosystem optimizer with a deep learning (IRA-AEODL) technique on UAV networks. The presented IRA-AEODL technique aims to effectually allot the resources in wireless UAV networks. In this case, the IRA-AEODL technique focuses on the maximization of system utility over all users, combined user association, energy scheduling, and trajectory design. To optimally allocate the UAV policies, the stacked sparse autoencoder (SSAE) model is used in the UAV networks. For the hyperparameter tuning process, the AEO algorithm is used for enhancing the performance of the SSAE model. The experimental results of the IRA-AEODL technique are examined under different aspects and the outcomes stated the improved performance of the IRA-AEODL approach over recent state of art approaches.

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Gou, Xiaogang, Zhaojie Sun, and Kaiyuan Huang. "UAV-Aided Dual-User Wireless Power Transfer: 3D Trajectory Design and Energy Optimization." Sensors 23, no. 6 (March 10, 2023): 2994. http://dx.doi.org/10.3390/s23062994.

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Unmanned aerial vehicles (UAVs) have been widely considered to enhance the communication coverage, as well as the wireless power transfer (WPT) of energy-constrained communication networks to prolong their lifetime. However, the trajectory design of a UAV in such a system remains a key problem, especially considering the three-dimensional (3D) feature of the UAV. To address this issue, a UAV-assisted dual-user WPT system was investigated in this paper, where a UAV-mounted energy transmitter (ET) flies in the air to broadcast wireless energy to charge the energy receivers (ERs) on the ground. By optimizing the UAV’s 3D trajectory toward a balanced tradeoff between energy consumption and WPT performance, the energy harvested by all ERs during a given mission period was maximized. The above goal was achieved through the following detailed designs. On the one hand, on the basis of previous research results, there is a one-to-one correspondence between the UAV’s abscissa and height, so only the relationship between the height and time was focused on in this work to obtain the UAV’s optimal 3D trajectory. On the other hand, the idea of calculus was employed to calculate the total harvested energy, leading to the proposed high-efficiency trajectory design. Finally, the simulation results demonstrated that this contribution is capable of enhancing the energy supply by carefully designing the 3D trajectory of the UAV, compared to its conventional counterpart. In general, the above-mentioned contribution could be a promising way for UAV-aided WPT in the future Internet of Things (IoT) and wireless sensor networks (WSNs).

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Pierucci, Laura. "Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks." Applied Sciences 12, no. 2 (January 16, 2022): 895. http://dx.doi.org/10.3390/app12020895.

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Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

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Poudel, Sabitri, and Sangman Moh. "Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications." Sensors 21, no. 8 (April 17, 2021): 2839. http://dx.doi.org/10.3390/s21082839.

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In unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs), a UAV is employed as a mobile sink to gather data from sensor nodes. Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks. In emergency applications, timely data collection from sensor nodes and transferal of the data to the base station (BS) is a prime requisite. The timely and safe path of UAV is one of the fundamental premises for effective UWSN operations. It is essential and challenging to identify a suitable path in an environment comprising various obstacles and to ensure that the path can efficiently reach the target point. This paper proposes a hybrid path planning (HPP) algorithm for efficient data collection by assuring the shortest collision-free path for UAV in emergency environments. In the proposed HPP scheme, the probabilistic roadmap (PRM) algorithm is used to design the shortest trajectory map and the optimized artificial bee colony (ABC) algorithm to improve different path constraints in a three-dimensional environment. Our simulation results show that the proposed HPP outperforms the PRM and conventional ABC schemes significantly in terms of flight time, energy consumption, convergence time, and flight path.

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Rahman, Shakila, Jahid Hasan Rony, Jia Uddin, and Md Abdus Samad. "Real-Time Obstacle Detection with YOLOv8 in a WSN Using UAV Aerial Photography." Journal of Imaging 9, no. 10 (October 10, 2023): 216. http://dx.doi.org/10.3390/jimaging9100216.

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Nowadays, wireless sensor networks (WSNs) have a significant and long-lasting impact on numerous fields that affect all facets of our lives, including governmental, civil, and military applications. WSNs contain sensor nodes linked together via wireless communication links that need to relay data instantly or subsequently. In this paper, we focus on unmanned aerial vehicle (UAV)-aided data collection in wireless sensor networks (WSNs), where multiple UAVs collect data from a group of sensors. The UAVs may face some static or moving obstacles (e.g., buildings, trees, static or moving vehicles) in their traveling path while collecting the data. In the proposed system, the UAV starts and ends the data collection tour at the base station, and, while collecting data, it captures images and videos using the UAV aerial camera. After processing the captured aerial images and videos, UAVs are trained using a YOLOv8-based model to detect obstacles in their traveling path. The detection results show that the proposed YOLOv8 model performs better than other baseline algorithms in different scenarios—the F1 score of YOLOv8 is 96% in 200 epochs.

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Eom, Subin, Hoon Lee, Junhee Park, and Inkyu Lee. "UAV-Aided Wireless Communication Designs With Propulsion Energy Limitations." IEEE Transactions on Vehicular Technology 69, no. 1 (January 2020): 651–62. http://dx.doi.org/10.1109/tvt.2019.2952883.

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Fontanesi, Gianluca, Anding Zhu, and Hamed Ahmadi. "Outage Analysis for Millimeter-Wave Fronthaul Link of UAV-Aided Wireless Networks." IEEE Access 8 (2020): 111693–706. http://dx.doi.org/10.1109/access.2020.3001342.

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Taneja, Ashu, Shalli Rani, and Norbert Herencsar. "Energy aware solution for IRS-aided UAV communication in 6G wireless networks." Sustainable Energy Technologies and Assessments 58 (August 2023): 103318. http://dx.doi.org/10.1016/j.seta.2023.103318.

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Tan, Zhiqiang, Limin Xiao, Xinyi Tang, Ming Zhao, and Yunzhou Li. "A FL-Based Radio Map Reconstruction Approach for UAV-Aided Wireless Networks." Electronics 12, no. 13 (June 26, 2023): 2817. http://dx.doi.org/10.3390/electronics12132817.

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Radio maps, which can provide metrics for signal strength at any location in a geographic space, are useful for many applications of 6G technologies, including UAV-assisted communication, network planning, and resource allocation. However, current crowd-sourced reconstruction methods necessitate large amounts of privacy-sensitive user data and entail the training of all data with large models, especially in deep learning. This poses a threat to user privacy, reducing the willingness to provide data, and consuming significant server resources, rendering the reconstruction of radio maps on resource-constrained UAVs challenging. To address these limitations, a self-supervised federated learning model called RadioSRCNet is proposed. The model utilizes a super-resolution (SR)-based network and feedback training strategy to predict the pathloss for continuous positioning. In our proposition, users retain the original data locally for training, acting as clients, while the UAV functions as a server to aggregate non-sensitive data for radio map reconstruction in a federated learning (FL) manner. We have employed a feedback training strategy to accelerate convergence and alleviate training difficulty. In addition, we have introduced an arbitrary position prediction (APP) module to decrease resource consumption in clients. This innovative module struck a balance between spatial resolution and computational complexity. Our experimental results highlight the superiority of our proposed framework, as our model achieves higher accuracy while incurring less communication overheads in a computationally and storage-efficient manner as compared to other deep learning methods.

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AlJubayrin, Saad, Fahd N. Al-Wesabi, Hadeel Alsolai, Mesfer Al Duhayyim, Mohamed K. Nour, Wali Ullah Khan, Asad Mahmood, Khaled Rabie, and Thokozani Shongwe. "Energy Efficient Transmission Design for NOMA Backscatter-Aided UAV Networks with Imperfect CSI." Drones 6, no. 8 (July 28, 2022): 190. http://dx.doi.org/10.3390/drones6080190.

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The recent combination of ambient backscatter communication (ABC) with non-orthogonal multiple access (NOMA) has shown great potential for connecting large-scale Internet of Things (IoT) in future unmanned aerial vehicle (UAV) networks. The basic idea of ABC is to provide battery-free transmission by harvesting the energy of existing RF signals of WiFi, TV towers, and cellular base stations/UAV. ABC uses smart sensor tags to modulate and reflect data among wireless devices. On the other side, NOMA makes possible the communication of more than one IoT on the same frequency. In this work, we provide an energy efficient transmission design ABC-aided UAV network using NOMA. This work aims to optimize the power consumption of a UAV system while ensuring the minimum data rate of IoT. Specifically, the transmit power of UAVs and the reflection coefficient of the ABC system are simultaneously optimized under the assumption of imperfect channel state information (CSI). Due to co-channel interference among UAVs, imperfect CSI, and NOMA interference, the joint optimization problem is formulated as non-convex, which involves high complexity and makes it hard to obtain the optimal solution. Thus, it is first transformed and then solved by a sub-gradient method with low complexity. In addition, a conventional NOMA UAV framework is also studied for comparison without involving ABC. Numerical results demonstrate the benefits of using ABC in a NOMA UAV network compared to the conventional UAV framework.

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Lan, Tingting, Danyang Qin, and Guanyu Sun. "Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks." ISPRS International Journal of Geo-Information 10, no. 7 (June 23, 2021): 426. http://dx.doi.org/10.3390/ijgi10070426.

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In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

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Qin, Huaiyu, Buhui Zhao, Leijun Xu, and Xue Bai. "Petri-Net Based Multi-Objective Optimization in Multi-UAV Aided Large-Scale Wireless Power and Information Transfer Networks." Remote Sensing 13, no. 13 (July 3, 2021): 2611. http://dx.doi.org/10.3390/rs13132611.

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Power consumption in wireless sensor networks is high, and the lifetime of a battery has become a bottleneck, restricting network performance. Wireless power transfer with a ground mobile charger is vulnerable to interference from the terrain and other factors, and hence it is difficult to deploy in practice. Accordingly, a novel paradigm is adopted where a multi-UAV (unmanned aerial vehicle) with batteries can transfer power and information to SDs (sensor devices) in a large-scale sensor network. However, there are discrete events, continuous process, time delay, and decisions in such a complicated system. From the perspective of a hybrid system, a hybrid colored cyber Petri net system is proposed here to depict and analyze this problem. Furthermore, the energy utilization rate and information collection time delay are conflict with each other; therefore, UAV-aided wireless power and information transfer is formulated as a multi-objective optimization problem. For this reason, the MAC-NSGA II (multiple ant colony-nondominated sorting genetic algorithm II) is proposed in this work. Firstly, the optimal trajectory of multiple UAVs was obtained, and on this basis, the above two objectives were optimized simultaneously. Large-scale simulation results show that the proposed algorithm is superior to NSGA II and MOEA/D in terms of energy efficiency and information collection delay.

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Wang, Gicheol, Byoung-Sun Lee, Jae Young Ahn, and Gihwan Cho. "A UAV-Aided Cluster Head Election Framework and Applying Such to Security-Driven Cluster Head Election Schemes: A Survey." Security and Communication Networks 2018 (June 19, 2018): 1–17. http://dx.doi.org/10.1155/2018/6475927.

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UAS (Unmanned Aerial Systems) are now drawing a lot of attention from academic and research fields as well as the general public. The UAS is expected to provide many promising applications such as intelligent transportation system, disaster management, search and rescue, public safety, smart delivery, wild species monitoring, and wireless service area extension. More specifically, as a part of the wireless service extension, we deal with the information dissemination and collection using a UAV in this paper. In this application, because the UAV communicates with each CH (Cluster Head) to collect data from sensor nodes or to disseminate information to the sensor nodes, well-behaved and qualified nodes should be elected as CHs and their integrity should be preserved. Even though a UAV makes the information dissemination and collection process efficient in a WSN, we can make the UAV help the election of new CHs to mitigate the threat of compromised CHs. To this aim, we first propose a UAV-aided CH election framework where a UAV delivers the critical information collected from sensors to the sink, and the sink reselects a set of well-behaved and qualified CHs considering the information. Then, we classify the existing security-driven CH election schemes into several categories and explain the principle of each category and its representative schemes. For each representative scheme, we also explain how to adapt it into the UAV-aided CH election framework. Next, we identify some desirable security properties that a CH election scheme should provide and reveal the security level that each representative scheme reaches for the desirable security properties. Next, we compare communication and computation overhead of the security-driven CH election schemes in terms of the big O notation. In conclusion, we reveal what we have learned from this survey work and provide a future work item.

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Chen, Chengbin, Jin Xiang, Zhuoya Ye, Wanyi Yan, Suiling Wang, Zhensheng Wang, Pingping Chen, and Min Xiao. "Deep Learning-Based Energy Optimization for Edge Device in UAV-Aided Communications." Drones 6, no. 6 (June 3, 2022): 139. http://dx.doi.org/10.3390/drones6060139.

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Edge devices (EDs) carry limited energy, but 6th generation mobile networks (6G) communication will consume more energy. The unmanned aerial vehicle (UAV)-aided wireless communication network can provide communication links to EDs without a signal. However, with the time-lag system, the EDs cannot dynamically adjust the emission energy because the dynamic UAV coordinates cannot be accurately acquired. In addition, the fixed emission energy makes the EDs have poor endurance. To address this challenge, in this paper, we propose a deep learning-based energy optimization algorithm (DEO) to dynamically adjust the emission energy of the ED so that the received energy of the mobile relay UAV is, as much as possible, equal to the sensitivity of the receiver. Specifically, the edge server provides the computing platform and uses deep learning (DL) to predict the location information of the relay UAV in dynamic scenarios. Then, the ED emission energy is adjusted according to the predicted position. It enables the ED to communicate reliably with the mobile relay UAV at minimum energy. We analyze the performance of a variety of predictive networks under different time-delay systems through experiments. The results show that the Weighted Mean Absolute Percentage Error (WMAPE) of this algorithm is 0.54%, 0.80% and 1.15% under the effect of a communication delay of 0.4 s, 0.6 s and 0.8 s, respectively.

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Janji, Salim, and Pawel Sroka. "RIS-aided Multi-hop Backhauling for 5G/6G UAV-assisted Access Points." Journal of Telecommunications and Information Technology, no. 2 (June 29, 2023): 63–69. http://dx.doi.org/10.26636/jtit.2023.171523.

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Drones are considered to be an important part of future 6G telecommunication systems. Thanks to their quick deployment potential, they provide additional connectivity options in the form of a ﬂying hotspot. However, in such use cases, they typically require a wireless backhaul link to facilitate their proper operation, which might be a challenging task in dense urban environments. One of the potential methods that may be relied upon to connect such nodes is the integrated access and backhaul (IAB) approach, where part of the spectrum allocated to users accessing the base station is used for wireless backhauling. Thus, in this work, we consider the problem of establishing a multi-hop wireless backhaul link following the IAB concept, with the aid of drone relay stations (DRSs) and reconﬁgurable intelligent surfaces (RISs). We formulate the problem of coverage improvement with a ﬁxed number of relays, assuming certain throughput requirements for the backhaul link. The simulations show that the use of RISs oﬀers a coverage improvement in such a scenario or a reduction in the number of nodes involved in ensuring the required backhaul performance.

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Bacanli, Salih Safa, Enas Elgeldawi, Begümhan Turgut, and Damla Turgut. "UAV Charging Station Placement in Opportunistic Networks." Drones 6, no. 10 (October 9, 2022): 293. http://dx.doi.org/10.3390/drones6100293.

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Unmanned aerial vehicles (UAVs) are now extensively used in a wide variety of applications, including a key role within opportunistic wireless networks. These types of opportunistic networks are considered well suited for infrastructure-less areas, or urban areas with overloaded cellular networks. For these networks, UAVs are envisioned to complement and support opportunistic network performance; however, the short battery life of commercial UAVs and their need for frequent charging can limit their utility. This paper addresses the challenge of charging station placement in a UAV-aided opportunistic network. We implemented three clustering approaches, namely, K-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and random clustering, with each clustering approach being examined in combination with Epidemic, Spray and Wait, and State-Based Campus Routing (SCR) routing protocols. The simulation results show that determining the charging station locations using K-means clustering with three clusters showed lower message delay and higher success rate than deciding the charging station location either randomly or using DBSCAN regardless of the routing strategy employed between nodes.

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Alsolai, Hadeel, Jaber S. Alzahrani, Mohammed Maray, Mohammed Alghamdi, Ayman Qahmash, Mrim M. Alnfiai, Amira Sayed A. Aziz, and Anwer Mustafa Hilal. "Enhanced Artificial Gorilla Troops Optimizer Based Clustering Protocol for UAV-Assisted Intelligent Vehicular Network." Drones 6, no. 11 (November 16, 2022): 358. http://dx.doi.org/10.3390/drones6110358.

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The increasing demands of several emergent services brought new communication problems to vehicular networks (VNs). It is predicted that the transmission system assimilated with unmanned aerial vehicles (UAVs) fulfills the requirement of next-generation vehicular network. Because of its higher flexible mobility, the UAV-aided vehicular network brings transformative and far-reaching benefits with extremely high data rates; considerably improved security and reliability; massive and hyper-fast wireless access; much greener, smarter, and longer 3D communications coverage. The clustering technique in UAV-aided VN is a difficult process because of the limited energy of UAVs, higher mobility, unstable links, and dynamic topology. Therefore, this study introduced an Enhanced Artificial Gorilla Troops Optimizer–based Clustering Protocol for a UAV-Assisted Intelligent Vehicular Network (EAGTOC-UIVN). The goal of the EAGTOC-UIVN technique lies in the clustering of the nodes in UAV-based VN to achieve maximum lifetime and energy efficiency. In the presented EAGTOC-UIVN technique, the EAGTO algorithm was primarily designed by the use of the circle chaotic mapping technique. Moreover, the EAGTOC-UIVN technique computes a fitness function with the inclusion of multiple parameters. To depict the improved performance of the EAGTOC-UIVN technique, a widespread simulation analysis was performed. The comparison study demonstrated the enhancements of the EAGTOC-UIVN technique over other recent approaches.

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Ma, Xiaoyan, Tianyi Liu, Song Liu, Rahim Kacimi, and Riadh Dhaou. "Priority-Based Data Collection for UAV-Aided Mobile Sensor Network." Sensors 20, no. 11 (May 27, 2020): 3034. http://dx.doi.org/10.3390/s20113034.

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In this work, we study data collection in multiple unmanned aerial vehicle (UAV)-aided mobile wireless sensor networks (WSNs). The network topology is changing due to the mobility of the UAVs and the sensor nodes, so the design of efficient data collection protocols is a major concern. We address such high dynamic network and propose two mechanisms: prioritized-based contact-duration frame selection mechanism (PCdFS), and prioritized-based multiple contact-duration frame selection mechanisms (PMCdFS) to build collision-free scheduling and balance the nodes between the multi-UAV respectively. Based on the two mechanisms, we proposed a Balance algorithm to conduct the collision-free communication between the mobile nodes and the multi-UAVs. Two key design ideas for a Balance algorithm are: (a) no need of higher priority for those nodes that have lower transmission rate between them and the UAV and (b) improve the communication opportunity for those nodes that have shorter contact duration with the UAVs. We demonstrate the performance of proposed algorithms through extensive simulations, and real experiments. These experiments using 15 mobile nodes at a path with 10 intersections and 1 island, present that network fairness is efficiently enhanced. We also confirm the applicability of proposed algorithms in a challenging and realistic scenario through numerous experiments on a path at Tongji campus in Shanghai, China.

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Che, Yueling, Zeyu Zhao, Sheng Luo, Kaishun Wu, Lingjie Duan, and Victor C. M. Leung. "UAV-Aided Wireless Energy Transfer for Sustaining Internet of Everything in 6G." Drones 7, no. 10 (October 9, 2023): 628. http://dx.doi.org/10.3390/drones7100628.

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Unmanned aerial vehicles (UAVs) are a promising technology used to provide on-demand wireless energy transfer (WET) and sustain various low-power ground devices (GDs) for the Internet of Everything (IoE) in sixth generation (6G) wireless networks. However, an individual UAV has limited battery energy, which may confine the required wide-range mobility in a complex IoE scenario. Furthermore, the heterogeneous GDs in IoE applications have distinct non-linear energy harvesting (EH) properties and diversified energy and/or communication demands, which poses new requirements on the WET and trajectory design of UAVs. In this article, to reflect the non-linear EH properties of GDs, we propose the UAV’s effective-WET zone (E-zone) above each GD, where a GD is assured to harvest non-zero energy from the UAV only when the UAV transmits into the E-zone. We then introduce the free space optics (FSO) powered UAV with enhanced mobility, and propose its adaptive WET for the GDs with non-linear EH. Considering the time urgency of the different energy demands of the GDs, we propose a new metric called the energy latency time, which is the time duration that a GD can wait before becoming fully charged. By proposing the energy-demand aware UAV trajectory, we further present a novel hierarchical WET scheme to meet the GDs’ diversified energy latency time. Moreover, to efficiently sustain IoE communications, the multi-UAV enabled WET is employed by unleashing their cooperative diversity gain and the joint design with the wireless information transfer (WIT). The numerical results show that our proposed multi-UAV cooperative WET scheme under the energy-aware trajectory design achieves the shortest task completion time as compared to the state-of-the-art benchmarks. Finally, the new directions for future research are also provided.

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Liu, Yuan, Ke Xiong, Yang Lu, Qiang Ni, Pingyi Fan, and Khaled Ben Letaief. "UAV-Aided Wireless Power Transfer and Data Collection in Rician Fading." IEEE Journal on Selected Areas in Communications 39, no. 10 (October 2021): 3097–113. http://dx.doi.org/10.1109/jsac.2021.3088693.

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Wei, Menghan, Youjia Chen, and Ming Ding. "On the Performance of UAV-Aided Content Caching in Small-Cell Networks with Joint Transmission." Electronics 10, no. 9 (April 28, 2021): 1040. http://dx.doi.org/10.3390/electronics10091040.

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Unmanned aerial vehicles (UAVs), featured by the high-mobility and high-quality propagation environment, have shown great potential in wireless communication applications. In this paper, a novel UAV-aided small-cell content caching network is proposed and analyzed, where joint transmission (JT) is considered in the dense small-cell networks and mobile UAVs are employed to shorten the serving distance. The system performance is evaluated in terms of the average cache hit probability and the ergodic transmission rate. From the analytical results, we find that (i) the proposed UAV-aided small-cell network shows superior caching performance and, even with a small density of UAVs the system’s cache hit probability, can be improved significantly; (ii) the content’s optimal caching probability to maximize the cache hit probability is proportional to the (K+1)-th root of its request probability, where K is the number of small-cell base stations that serve each user by JT; (iii) caching the most popular content in UAVs may lead to a low transmission rate due to the limited resource offered by the low-density UAVs. Simulation results are presented to validate the theoretical results and the performance gain achieved by the optimal caching strategy.

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Poudel, Sabitri, and Sangman Moh. "Energy-Efficient and Fast MAC Protocol in UAV-Aided Wireless Sensor Networks for Time-Critical Applications." Sensors 20, no. 9 (May 5, 2020): 2635. http://dx.doi.org/10.3390/s20092635.

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Unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs) can be effectively used for time-critical sensing applications. UAVs can be used to collect the sensed data from sensors and transfer them to a base station. The real-time transfer of data is highly desired in the time-critical applications. However, the medium access control (MAC) protocols designed for UWSNs so far are primarily focused on the efficient use of UAVs to collect data in the sensing areas. In this paper, we propose an energy-efficient and fast MAC (EF-MAC) protocol in UWSNs for time-critical sensing applications. EF-MAC adopts carrier sense multiple access (CSMA) for the registration of sensor nodes with a UAV and time division multiple access (TDMA) with variable slot time for the transmission of collected data. The UAV is equipped with two transceivers to minimize both energy consumption and delay in air-to-ground communication. The energy consumption and delay are formally analyzed and the performance of EF-MAC is evaluated via extensive simulation. The simulation results show that the proposed EF-MAC outperforms the conventional MAC protocols in terms of energy efficiency and communication delay.

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Muhammad Hashir, Syed, Arefe Mehrabi, Mohammad Robat Mili, Mohamamd Javad Emadi, Derrick Wing Kwan Ng, and Ioannis Krikidis. "Performance Trade-Off in UAV-Aided Wireless-Powered Communication Networks via Multi-Objective Optimization." IEEE Transactions on Vehicular Technology 70, no. 12 (December 2021): 13430–35. http://dx.doi.org/10.1109/tvt.2021.3122077.

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SAY, Sotheara, Mohamad Erick ERNAWAN, and Shigeru SHIMAMOTO. "Cooperative Path Selection Framework for Effective Data Gathering in UAV-Aided Wireless Sensor Networks." IEICE Transactions on Communications E99.B, no. 10 (2016): 2156–67. http://dx.doi.org/10.1587/transcom.2016atp0012.

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43

Jia, Huaiqi, Ying Wang, Man Liu, and Yuanbin Chen. "Sum-Rate Maximization for UAV Aided Wireless Power Transfer in Space-Air-Ground Networks." IEEE Access 8 (2020): 216231–44. http://dx.doi.org/10.1109/access.2020.3040868.

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Wu, Pengfei, Fu Xiao, Haiping Huang, and Ruchuan Wang. "Load Balance and Trajectory Design in Multi-UAV Aided Large-Scale Wireless Rechargeable Networks." IEEE Transactions on Vehicular Technology 69, no. 11 (November 2020): 13756–67. http://dx.doi.org/10.1109/tvt.2020.3026788.

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Mayor, Vicente, Rafael Estepa, Antonio Estepa, and German Madinabeitia. "Deploying a Reliable UAV-Aided Communication Service in Disaster Areas." Wireless Communications and Mobile Computing 2019 (April 8, 2019): 1–20. http://dx.doi.org/10.1155/2019/7521513.

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When telecommunication infrastructure is damaged by natural disasters, creating a network that can handle voice channels can be vital for search and rescue missions. Unmanned Aerial Vehicles (UAV) equipped with WiFi access points could be rapidly deployed to provide wireless coverage to ground users. This WiFi access network can in turn be used to provide a reliable communication service to be used in search and rescue missions. We formulate a new problem for UAVs optimal deployment which considers not only WiFi coverage but also the mac sublayer (i.e., quality of service). Our goal is to dispatch the minimum number of UAVs for provisioning a WiFi network that enables reliable VoIP communications in disaster scenarios. Among valid solutions, we choose the one that minimizes energy expenditure at the user’s WiFi interface card in order to extend ground user’s smartphone battery life as much as possible. Solutions are found using well-known heuristics such as K-means clusterization and genetic algorithms. Via numerical results, we show that the IEEE 802.11 standard revision has a decisive impact on the number of UAVs required to cover large areas, and that the user’s average energy expenditure (attributable to communications) can be reduced by limiting the maximum altitude for drones or by increasing the VoIP speech quality.

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Nazib, Rezoan Ahmed, and Sangman Moh. "Energy-Efficient and Fast Data Collection in UAV-Aided Wireless Sensor Networks for Hilly Terrains." IEEE Access 9 (2021): 23168–90. http://dx.doi.org/10.1109/access.2021.3056701.

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Park, Junhee, Hoon Lee, Subin Eom, and Inkyu Lee. "UAV-Aided Wireless Powered Communication Networks: Trajectory Optimization and Resource Allocation for Minimum Throughput Maximization." IEEE Access 7 (2019): 134978–91. http://dx.doi.org/10.1109/access.2019.2941278.

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Griffin Siji, Fagbohunm. "An improved energy-efficient data clustering in UAV-Aided Wireless Sensor Networks for uneven topology." Discovery 59, no. 333 (December 9, 2023): 1–25. http://dx.doi.org/10.54905/disssi.v59i333.e114d1355.

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Nguyen, Tri-Hai, Luong Vuong Nguyen, L. Minh Dang, Vinh Truong Hoang, and Laihyuk Park. "TD3-Based Optimization Framework for RSMA-Enhanced UAV-Aided Downlink Communications in Remote Areas." Remote Sensing 15, no. 22 (November 8, 2023): 5284. http://dx.doi.org/10.3390/rs15225284.

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The need for reliable wireless communication in remote areas has led to the adoption of unmanned aerial vehicles (UAVs) as flying base stations (FlyBSs). FlyBSs hover over a designated area to ensure continuous communication coverage for mobile users on the ground. Moreover, rate-splitting multiple access (RSMA) has emerged as a promising interference management scheme in multi-user communication systems. In this paper, we investigate an RSMA-enhanced FlyBS downlink communication system and formulate an optimization problem to maximize the sum-rate of users, taking into account the three-dimensional FlyBS trajectory and RSMA parameters. To address this continuous non-convex optimization problem, we propose a TD3-RFBS optimization framework based on the twin-delayed deep deterministic policy gradient (TD3). This framework overcomes the limitations associated with the overestimation issue encountered in the deep deterministic policy gradient (DDPG), a well-known deep reinforcement learning method. Our simulation results demonstrate that TD3-RFBS outperforms existing solutions for FlyBS downlink communication systems, indicating its potential as a solution for future wireless networks.

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Wang, Qubeijian, Hong-Ning Dai, Xuran Li, Mahendra K. Shukla, and Muhammad Imran. "Artificial noise aided scheme to secure UAV-assisted Internet of Things with wireless power transfer." Computer Communications 164 (December 2020): 1–12. http://dx.doi.org/10.1016/j.comcom.2020.09.017.

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Journal articles on the topic 'UAV-aided Wireless Networks'

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