Article
Computer Science, Information Systems
Hua Yan, Yunfei Chen, Shuang-Hua Yang
Summary: The translated passage highlights the importance of accurate and convenient energy consumption models for rotary-wing UAVs in communication designs. The author introduces a simple model with closed-form expression based on initial velocity, acceleration, and time duration, and analyses UAV flight control parameters using this model. Numerical results demonstrate the validity and reliability of the proposed model.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Hangmei Rao, Sa Xiao, Shihao Yan, Jianquan Wang, Wanbin Tang
Summary: This work uses a UAV as a jammer to aid covert communication. An optimization problem is formulated to jointly design the UAV's trajectory and Alice's transmit power, which is solved by a geometric method that outperforms conventional iterative methods in achieving higher covert rate and lower complexity.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Wei Jian Lau, Joanne Mun-Yee Lim, Chun Yong Chong, Nee Shen Ho, Thomas Wei Min Ooi
Summary: This paper analyzes the performance of a UAV swarm network by characterizing the effects of UAV-to-UAV interference in terms of SINR. The model considers both deterministic and stochastic channel processes and incorporates hybrid LoS channels. The effects of network parameters on various KPIs are studied, and the model is used to evaluate the temporal evolutions of network outage probability given the UAV trajectories. The main advantage of the model is its ability to analyze the baseline outage probabilities of multi-UAV deployments.
Article
Chemistry, Analytical
Francisco Oliveira, Miguel Luis, Susana Sargento
Summary: UAV networks are a versatile technology applicable in both military and civilian settings, with the use of machine learning algorithms showing promising results in reducing the number of users without a connection and achieving a more balanced traffic redistribution. Accuracy of prediction plays a crucial role in determining the success of the algorithm and the deployment of UAVs.
Article
Agricultural Engineering
Miguel Noguera, Arturo Aquino, Juan M. Ponce, Antonio Cordeiro, Jose Silvestre, Rocio Calderon, Maria da Encarnacao Marcelo, Pedro Jordao, Jose M. Andujar
Summary: This research aimed to develop an efficient method for NPK foliar content retrieval in olive trees using multispectral images from a UAV. Various retrieval techniques were evaluated, with the artificial neural network (ANN) approach proving to be the most effective for the experimental conditions.
BIOSYSTEMS ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Jinchen He, Jiayuan Lin, Xianwei Zhang, Xiaohan Liao
Summary: Estimating the surface water volume of tufa lake group using UAV remote sensing and ANN models is crucial for protecting tufa landscapes.
Article
Computer Science, Information Systems
Wen Wang, Wanli Ni, Hui Tian, Yonina C. Eldar, Dusit Niyato
Summary: This letter proposes a UAV-mounted multi-functional reconfigurable intelligent surface (MF-RIS) to combat eavesdropping attacks. By jointly optimizing the transmit beamforming, reflection matrix, and deployment location of the MF-RIS, the proposed system enhances the received signal at the legitimate user while generating destructive interference for eavesdroppers.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Sixing Yin, F. Richard Yu
Summary: This article focuses on a downlink cellular network where multiple unmanned aerial vehicles (UAVs) act as aerial base stations for ground users. The researchers propose a multiagent reinforcement learning approach to optimize resource allocation and trajectory design in a decentralized manner. Simulation results demonstrate the efficiency and effectiveness of the proposed methods in achieving overall throughput and fairness.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Wei Wang, Nan Cheng, Yiliang Liu, Haibo Zhou, Xiaodong Lin, Xuemin Shen
Summary: This paper investigates the successful content delivery (SCD) performance in UAV integrated terrestrial cellular networks, showing that optimizing UAV density and height can lead to higher performance.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Andrey V. Savkin, Wei Ni, Mohsen Eskandari
Summary: This paper presents a new cellular-assisted radio surveillance and tracking technique using a UAV as the mobile receiver and a static cellular ground base station as the illuminating source. The resolution of the radio surveillance and imaging depends on the relative positions and motions of the UAV, base station, and target. A novel UAV navigation law is developed to ensure that the range resolution, azimuth resolution, and distance between the UAV and the moving target are below given upper limits after some time. Simulation results validate the effectiveness of the proposed navigation law.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Zhe Song, Jianping An, Haichuan Ding, Huaiyu Dai
Summary: In this study, we propose a new relay probing strategy for UAV mmWave A2G communications to maximize the expected achievable throughput. Our design takes into account beam training overhead, limited neighboring UAVs, finite UAV codebook sizes, and neighboring UAV orientations. We also derive a closed-form expression for the distribution of achievable throughput and present extensive simulation results to validate our analysis and the effectiveness of the relay probing strategy.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Telecommunications
Dan Deng, Xingwang Li, Varun Menon, Md Jalil Piran, Hui Chen, Mian Ahmad Jan
Summary: This paper proposes a reinforcement learning-based optimization algorithm to maximize the secrecy sum rate in NOMA-UAV networks. Through successive convex approximations and extensive exploration of the wireless environment, it achieves optimized power allocation and UAV location transition strategy even without wireless channel state information.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Telecommunications
Dan Deng, Xingwang Li, Varun Menon, Md Jalil Piran, Hui Chen, Mian Ahmad Jan
Summary: This paper focuses on maximizing the secrecy sum rate under the constraint of the achievable rate of the legitimate channels in NOMA-UAV networks. It proposes a reinforcement learning-based alternative optimization algorithm to obtain the optimal power allocation and location transition strategy using successive convex approximations and exploration of the wireless environment.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Computer Science, Information Systems
Daniele Palossi, Nicky Zimmerman, Alessio Burrello, Francesco Conti, Hanna Mueller, Luca Maria Gambardella, Luca Benini, Alessandro Giusti, Jerome Guzzi
Summary: This research focuses on achieving complex tasks with nano-sized unmanned aerial vehicles, specifically in estimating and maintaining the relative 3-D pose of the UAV with respect to a person. The study utilizes a vision-based deep neural network and ultra-low power processor for real-time autonomous navigation, demonstrating excellent performance.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Environmental Sciences
Brenon Diennevam Souza Barbosa, Gabriel Araujo e Silva Ferraz, Luana Mendes dos Santos, Lucas Santos Santana, Diego Bedin Marin, Giuseppe Rossi, Leonardo Conti
Summary: This study evaluated the potential of using UAVs and RGB vegetation indices in monitoring coffee crops, finding that MPRI and GLI showed some correlation with LAI, but the correlation was weak. Additionally, the use of these indices can help managers make timely crop management decisions and save resources.
Editorial Material
Engineering, Electrical & Electronic
Mohammad Abdul Matin, Sotirios K. Goudos, Shaohua Wan, Panagiotis Sarigiannidis, Emmanouil M. Tentzeris
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING
(2023)
Article
Chemistry, Analytical
Aikaterini I. Griva, Achilles D. Boursianis, Shaohua Wan, Panagiotis Sarigiannidis, Konstantinos E. Psannis, George Karagiannidis, Sotirios K. Goudos
Summary: The implementation of smart networks has been greatly advanced by the development of IoT, with LoRa being a prominent technology due to its long-distance transmission capabilities with low power consumption. This study simulated various environments to assess network performance based on different factors and parameters. Path loss model, deployment area size, transmission power, spreading factor, number of nodes and gateways, and antenna gain significantly affect the energy consumption and data extraction rate of LoRa networks. The research performed simulations using the FLoRa framework in OMNeT++, investigating rural and urban environments, as well as a parking area model. The results emphasize the importance of optimizing key parameters for the deployment of smart networks.
Article
Chemistry, Multidisciplinary
Christos L. Stergiou, Elisavet Bompoli, Konstantinos E. Psannis
Summary: Due to its unique services, Cloud Computing attracts researchers to develop sustainable systems. It offers users the opportunity to access and manage information, applications, and data anytime, anywhere. Big Data, a service that includes large amounts of data produced by the Internet of Things, is also discussed in this work.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Efstratios Chatzoglou, Sotirios K. K. Goudos
Summary: The beam selection problem is a challenge in mmWave communications for 5G/B5G due to attenuation and penetration losses. Traditional exhaustive search approach cannot be completed within short contact times, while machine learning shows potential in solving this problem. In this study, we compare different ML methods and improve the accuracy by adding synthetic data and applying ensemble learning techniques.
Article
Chemistry, Multidisciplinary
Georgios M. Minopoulos, Vasileios A. Memos, Konstantinos D. Stergiou, Christos L. Stergiou, Konstantinos E. Psannis
Summary: A lesson learned from the pandemic is that social distancing saves lives. The current healthcare services are not sufficient to protect medical staff from infectious diseases, such as COVID-19. Therefore, there is a need to introduce new technologies, such as Virtual Reality, Augmented Reality, Artificial Intelligence, and Tactile Internet, to bring about a holistic change in the healthcare industry.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Multidisciplinary
Ioannis D. Bougas, Maria S. Papadopoulou, Achilles D. Boursianis, Spyridon Nikolaidis, Sotirios K. Goudos
Summary: Radio-frequency (RF) energy harvesting is a reliable and constantly available free energy source. A dual-band RF to DC rectifier circuit designed in the sub-6 GHz frequency range of the 5G band can provide energy for low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at 3.5 GHz and 5 GHz in the 5G cellular network's frequency band FR1, with a maximum power conversion efficiency of 53% when the output load is 1.74 kO and the input power is 12 dBm.
Article
Engineering, Electrical & Electronic
Sotirios P. Sotiroudis, Georgia Athanasiadou, George Tsoulos, Panagiotis Sarigiannidis, Christos G. Christodoulou, Sotirios K. Goudos
Summary: The usage of UAVs as FBSs for expanding coverage and assisting cellular networks in 5G and beyond is a promising technology. Path loss prediction is a crucial parameter in cellular network design, and ML-based predictions using ensemble learning techniques offer a more efficient alternative to deterministic ray-tracing models. Our proposed evolutionary tuned stacked ensemble method optimizes the ensemble as a whole, achieving better performance in path loss modeling in electromagnetics.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Biochemical Research Methods
Ilias Siniosoglou, Vasileios Argyriou, Panagiotis Sarigiannidis, Thomas Lagkas, Antonios Sarigiannidis, Sotirios K. K. Goudos, Shaohua Wan
Summary: Modern healthcare cyberphysical systems rely on distributed AI and Federated Learning to train ML and DL models for various medical fields while protecting sensitive information. However, the local training of federated models sometimes falls short, affecting their optimization and subsequent performance. This work proposes a post-processing pipeline to improve model fairness and accuracy in the FL environment.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Review
Chemistry, Multidisciplinary
Christos L. Stergiou, Maria P. Koidou, Konstantinos E. Psannis
Summary: This paper provides a meticulous survey of IoT and monitoring systems, discussing their combination and how it can improve certain types of healthcare monitoring systems in the cloud. It also addresses technical challenges of multimedia in IoT and proposes an algorithm approach for transmitting and processing video/image data through a cloud-based monitoring system. The experimental findings demonstrate that the proposed system is more reliable and secure, showing the efficiency of using a cloud management system operated over a digital twin scenario.
APPLIED SCIENCES-BASEL
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Lazaros A. Iliadis, Achilles D. Boursianis, Vasileios P. Rekkas, Zaharias D. Zaharis, Stavros Koulouridis, Sotirios K. Goudos
Summary: Autonomous driving will revolutionize transportation networks and bring numerous benefits, such as enhanced safety, reliable vehicle communication, and improved telecommunication. To enable a self-driving vehicle to navigate and perceive its surroundings, equipping it with a variety of sensors is essential. This study proposes the design of an aperture-coupled bowtie antenna using hunger games search optimization, which achieves satisfactory performance in terms of return loss, gain, and broadband operation from 76 GHz to 81 GHz.
2023 INTERNATIONAL WORKSHOP ON ANTENNA TECHNOLOGY, IWAT
(2023)
Article
Computer Science, Information Systems
Fan Ding, Yunying Ren, Sotirios Goudos, Ya Zhao
Summary: This paper explores the research path of public space renewal in historic city districts based on the perspective of community governance. Taking the historical public space of Lhasa city as an example, it analyzes the causes of characteristics of public space and the logical relationship with urban renewal and community governance. By applying a neural network evaluation model, it calculates scores for each indicator using cell rasterization, indicator classification, and population density estimation, determines the weight of each indicator using the entropy method, builds a multi-dimensional indicator system to evaluate public space satisfaction, and optimizes the pattern of historical public space by improving the spatial structure. In conclusion, this study emphasizes the importance of public space renewal for human-oriented development, community governance, and overall urban renewal in historic districts.
Article
Engineering, Electrical & Electronic
Jayakrishnan Vijayamohanan, Arjun Gupta, Oameed Noakoasteen, Sotirios K. K. Goudos, Christos G. Christodoulou
Summary: By using deep learning frameworks, the unreliable conventional algorithms for radio source detection in the presence of low SINR and less snapshots are addressed. Source detection is reformulated as a multi-class classification problem, where the input feature is extracted from the normalized upper triangle of the autocorrelation matrix sampled from a centro-symmetric linear array. Two detection algorithms, CNNDetector and RadioNet, are introduced and benchmarked against conventional algorithms. RadioNet can resolve the number of uncorrelated sources in the presence of correlated paths through pre-processing and forward backward spatial smoothing. Extensive evaluations demonstrate the efficacy and contributions of the introduced predictive models. To our knowledge, this is the first time the source detection problem has been resolved for L-1 sources using a deep learning framework in an antenna array of L elements.
IEEE OPEN JOURNAL OF SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
M. Rezwanul Mahmood, Mohammad Abdul Matin, Sotirios K. Goudos
Summary: This paper investigates machine learning approaches for receiver design in RIS-assisted multi-user MIMO systems to avoid complex channel information requirements.
Article
Computer Science, Information Systems
Sotirios K. Goudos, Panagiotis D. Diamantoulakis, Achilles D. Boursianis, Panagiotis Sarigiannidis, Konstantinos E. Psannis, Mohammad Abdul Matin, Shaohua Wan, George K. Karagiannidis
Summary: In this work, we address the problem of joint power allocation and user association for non-orthogonal multiple access (NOMA) in downlink networks based on quality-of-service. Due to its non-convex form and the large number of optimization variables, the problem is challenging and we propose two nature-inspired algorithms with low complexity for solving it. We investigate the impact of different network parameters on increasing users and show that evolutionary algorithms are effective in solving this problem, outperforming randomly generated solutions. Furthermore, the advantages of NOMA over OMA become more evident as the number of users increases.
