Article
Engineering, Electrical & Electronic
Joshua Trethowan, Zihao Wang, K. C. Wong
Summary: This study presents a novel bird deterrence solution using tethered UAVs arranged in a grid-like fashion. The simulation model evaluates the feasibility of different UAV arrangements and strategies against bird behavior, and introduces a bird energy expenditure model to quantify persistence and effort. The results indicate that a centralized multi-UAV control strategy can successfully deter both single and multiple bird flocks. Overall, this study proposes a viable and novel solution for bird deterrence in agriculture using tethered UAV platforms.
Article
Telecommunications
N. H. Ranchagoda, K. Sithamparanathan, M. Ding, A. Al-Hourani, K. M. Gomez
Summary: This paper proposes an Elevation Angle (EA) based two-ray mean path loss model for Air-to-Ground (A2G) channels, which accurately characterizes the path loss of A2G channels. The study investigates different altitudes, terrains, and polarizations, showing that the proposed EA-based two-ray model matches well with the ray-tracing simulation results. Furthermore, a comparison with other known path loss models is conducted, revealing an interesting relationship between the elevation angle and signal down-fades.
VEHICULAR COMMUNICATIONS
(2021)
Article
Telecommunications
Huafu Li, Liqin Ding, Yang Wang, Zhenyong Wang
Summary: In this letter, the authors investigate the air-to-ground (A2G) channel model and transmission performance for a cellular-connected massive multiple-input multiple-output unmanned aerial vehicle (UAV) swarm system. They propose a spatially and temporally correlated A2G channel model that focuses on non-isotropic scattering, line-of-sight (LoS) propagation, and moving scatterers. They also derive a closed-form signal-to-interference-and-noise ratio expression for uplink transmission, considering the effect of channel aging with strong LoS.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
William Xia, Sundeep Rangan, Marco Mezzavilla, Angel Lozano, Giovanni Geraci, Vasilii Semkin, Giuseppe Loianno
Summary: This paper proposes a general modeling methodology based on data-training a generative neural network for mmWave air-to-ground channels between UAVs and a cellular system. The proposed approach is able to capture complex statistical relations in the data and significantly outperforms standard 3GPP models.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Junyu Liu, Hongwei Zhang, Min Sheng, Yu Su, Shengwei Chen, Jiandong Li
Summary: This paper investigates the high-altitude air-to-ground channel characteristics for aerial base stations carried by fixed-wing unmanned aerial vehicles. It examines the stability of the A2G wireless links and proposes models for multipath and shadow fading. The research findings suggest that different distribution models are suitable for simulating the A2G wireless channel under various conditions.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Zhuangzhuang Cui, Ke Guan, Claude Oestges, Cesar Briso-Rodriguez, Bo Ai, Zhangdui Zhong
Summary: This paper focuses on the cluster-based characterization and modeling of air-to-ground (AG) propagation channels for unmanned aerial vehicles (UAVs) integrated with wireless communication. It proposes a novel cluster-based AG channel model and validates its accuracy.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Oluwatosin Ahmed Amodu, Chedia Jarray, Sherif Adeshina Busari, Mohamed Othman
Summary: Unmanned aerial vehicles (UAVs) and Terahertz (THz) communication are promising technologies for enhanced wireless performance. Research on the merger of these two technologies is gaining momentum, with the potential to meet the diverse application requirements in future wireless communication. Recent experimentation and modeling have shown the merits of THz-enabled UAV communication in critical and peculiar cases, revealing its great potential. This paper presents a literature survey on the experimental results, potential use cases, and research challenges of THz-UAV to provide insights into the opportunities in aerial wireless communications.
Review
Engineering, Civil
Junayed Pasha, Zeinab Elmi, Sumit Purkayastha, Amir M. Fathollahi-Fard, Ying-En Ge, Yui-Yip Lau, Maxim A. Dulebenets
Summary: Drones are becoming increasingly popular for their advanced mobility and have a wide range of applications in various sectors. Effective drone scheduling, which involves optimizing flight paths and considering other factors such as battery capacity, is crucial in overcoming the limitations of drones. However, there is a lack of systematic literature survey on drone scheduling and future research needs. This study conducts an extensive survey of scientific literature on drone scheduling, categorizing studies and providing mathematical models, findings, and future research needs, aiming to assist stakeholders in designing effective drone schedules.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Muhammad Yudhi Rezaldi, Ambar Yoganingrum, Nuraini Rahma Hanifa, Yoshiyuki Kaneda, Siti Kania Kushadiani, Abdurrakhman Prasetyadi, Budi Nugroho, Agus Men Riyanto
Summary: The 3D modeling method for tsunamis developed in this research addresses weaknesses of traditional methods and has advantages such as predicting wave endpoints, simulating original environments, and improving inundation height and area accuracy. Results can be used for creating evacuation routes and determining suitable shelter locations.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Jonghyeon Won, Do-Yup Kim, Young-Ik Park, Jang-Won Lee
Summary: This paper investigates the utilization of unmanned aerial vehicles (UAVs) in communication networks and the need to optimize their locations or trajectories. It introduces representative air-to-ground (A2G) channel models and reviews recent research on UAV placement and trajectory optimization. Based on the findings, future research directions are suggested.
Article
Engineering, Electrical & Electronic
Giulio Maria Bianco, Gaetano Marrocco
Summary: Long-range (LoRa) low-power wide-area network protocol is used to deploy ad hoc search and rescue (SaR) systems by enabling communication between body-worn radios and UAV-mounted radios. Understanding signal propagation in the environment is crucial for effective use of UAVs in these systems.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
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.
Article
Agriculture, Multidisciplinary
Shincheol Lee, Ji Sun Shin
Summary: In smart farming, technologies like IoT are improving efficiency while introducing security challenges. The proposed LV protocol and blockchain-based drone rental mechanism provide secure solutions, validated through security analysis and performance evaluation.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Environmental Sciences
Luiz Felipe Ramalho de Oliveira, H. Andrew Lassiter, Ben Wilkinson, Travis Whitley, Peter Ifju, Stephen R. Logan, Gary F. Peter, Jason G. Vogel, Timothy A. Martin
Summary: Unmanned aircraft systems (UAS) have rapidly advanced in technology, allowing for low-cost capture of high-resolution images for deriving three-dimensional photogrammetric point clouds. This study evaluates the quality of three-dimensional datasets from two cameras and one lidar sensor collected over a managed pine stand with different planting densities. The results show that the higher-quality camera photogrammetric data is sufficient for individual tree detection and height determination, but lidar data is best overall. The automated tree detection algorithm performed well with lidar data, but slightly fell short in comparison to manual mensuration within the lidar point cloud.
Article
Engineering, Electrical & Electronic
Hao Jiang, Baiping Xiong, Hongming Zhang, Ertugrul Basar
Summary: In this paper, a three-dimensional physics-based double reconfigurable intelligent surface (RIS) cooperatively assisted MIMO stochastic channel model is proposed for UAV-to-ground communication scenarios. The double-RIS, distributed on the surface of buildings, can assist the UAV transmitter in reflecting signals to the ground receiver (GR) and enhancing propagation by passive beamforming on the RISs. The proposed channel model effectively characterizes both large- and small-scale fading characteristics and derives critical propagation properties, demonstrating the necessity of introducing double-RIS into UAV-to-ground communication.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Bassel Al Homssi, Akram Al-Hourani
Summary: This research presents a framework for optimizing the uplink performance of dense satellite constellations using optimization techniques. The framework includes two key parameters: constellation altitude and satellite antenna beamwidth. By applying stochastic geometry tools, analytical models are derived to solve the uplink coverage problem considering user traffic demand. The results show that fine-tuning these parameters can significantly enhance network capacity.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Computer Science, Information Systems
Bisma Manzoor, Akram Al-Hourani, Bassel Al Homssi
Summary: Non-Terrestrial Networks (NTN) aims to provide global coverage in areas with limited terrestrial services using satellite and air-borne platforms. However, the long communication distance to satellite platforms leads to increased path-loss, posing a challenge to delivering NTN communications. This letter presents an analytic framework that captures the repetition behavior based on the probability of line-of-sight (LoS), allowing for coverage enhancements and optimization of frame success rate in IoT-over-Satellite networks.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Sruthy Skaria, Nermine Hendy, Akram Al-Hourani
Summary: In this article, we present a framework for utilizing machine learning in material identification based on radar signatures. The proposed framework, which utilizes multiple RX channels, achieved near-ideal classification accuracy in classifying six different materials and distinguishing three volume levels with accuracy above 98%.
IEEE SENSORS JOURNAL
(2023)
Article
Chemistry, Multidisciplinary
Aishani Mazumder, Chung Kim Nguyen, Thiha Aung, Mei Xian Low, Md. Ataur Rahman, Salvy P. Russo, Sherif Abdulkader Tawfik, Shifan Wang, James Bullock, Vaishnavi Krishnamurthi, Nitu Syed, Abhishek Ranjan, Ali Zavabeti, Irfan H. Abidi, Xiangyang Guo, Yongxiang Li, Taimur Ahmed, Torben Daeneke, Akram Al-Hourani, Sivacarendran Balendhran, Sumeet Walia
Summary: This study demonstrates the development of a miniaturized and low energy consumption optoelectronic synaptic system with long retention time and learning capabilities. It can perform real-time image recognition and memorization tasks.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Multidisciplinary Sciences
Tetiana Hourani, Alexis Perez-Gonzalez, Khashayar Khoshmanesh, Rodney Luwor, Adrian A. Achuthan, Sara Baratchi, Neil M. O'Brien-Simpson, Akram Al-Hourani
Summary: This study investigated macrophage autofluorescence as a distinct feature for classifying different macrophage phenotypes. The researchers constructed a dataset of 152,438 cell events and used supervised machine learning methods to detect phenotype-specific autofluorescence fingerprints. The results showed that this method can accurately classify macrophages into different phenotypes, with higher accuracy when fewer phenotypes are considered.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Akram Al-Hourani, Sivacarendran Balendhran, Sumeet Walia, Tetiana Hourani
Summary: With advancements in computer processing power and deep learning techniques, hyperspectral imaging is being explored for improved sensing applications. In this paper, a novel theoretical framework and an open source ultra-low-cost hyperspectral imaging platform based on the line scan method are developed. The platform is designed and fabricated using consumer-grade components, providing high spectral resolution and improved spatial resolution. A cost-effective testing method is also provided to validate the platform's performance.
Article
Computer Science, Information Systems
Imran Moez Khan, Andrew Thompson, Akram Al-Hourani, Kandeepan Sithamparanathan, Wayne S. T. Rowe
Summary: Complementing RSSI measurements with smartphone accelerometer measurements is a popular research direction in improving indoor localization systems. This study developed a novel conceptual framework that utilizes accelerometer measurements to classify smartphone's device pose and combines it with RSSI measurements. The framework, explored with neural networks and BLE experimental data, consistently improved the accuracy of the output localization classes.
Article
Chemistry, Analytical
Mutmainnah Hasib, Sithamparanathan Kandeepan, Wayne S. T. Rowe, Akram Al-Hourani
Summary: This paper provides a framework for modeling the DoA angle in satellite communications and effectively models the DoA angle by accurately calculating the Earth station's elevation angle. The paper also studies the impact of spatial correlation in the channel on well-known DoA estimation techniques and evaluates the DoA estimation performance using RMSE measurements.
Article
Telecommunications
Iza Shafinaz Mohamad Hashim, Akram Al-Hourani
Summary: In this letter, we propose a novel method to estimate the satellite visibility window in IoT devices based on simple Doppler measurements. We derive the Doppler measurement likelihood function and simplify it to an RMSE minimization problem. Using a stochastic optimizer, we estimate the orbital parameters of the serving satellite and predict the satellite visibility window. We evaluate the accuracy of the window estimation through Monte Carlo simulations and the intersection-over-union metric.
IEEE COMMUNICATIONS LETTERS
(2023)
Proceedings Paper
Telecommunications
Mutmainnah Hasib, Sithamparanathan Kandeepan, Wayne S. T. Rowe, Akram Al-Hourani
Summary: This paper investigates the direction-of-arrival (DoA) estimation method in multi-cluster systems with multiple antennas and spatial diversity. A new DoA estimation method is proposed by fusing channel-phase random variables from multiple clusters. Extensive Monte Carlo simulations demonstrate that the proposed method reduces estimation errors and improves performance through appropriate weight selection mechanisms.
2022 IEEE ASIA PACIFIC CONFERENCE ON WIRELESS AND MOBILE (APWIMOB)
(2022)
Proceedings Paper
Telecommunications
Niranjana Radhakrishnan, Nirmani Hewa Ranchagoda, Akram Al-Hourani, Sithamparanathan Kandeepan, Wayne S. T. Rowe
Summary: This paper proposes a hybrid technique that combines unsupervised clustering and a CNN-based system to address the interference problem in vehicular communications. Experimental results show that the proposed system performs reliably under various Signal-to-Noise-Ratio conditions.
2022 IEEE ASIA PACIFIC CONFERENCE ON WIRELESS AND MOBILE (APWIMOB)
(2022)
Proceedings Paper
Telecommunications
Munazza Shabbir, Sithamparanathan Kandeepan, Akram Al-Hourani, Wayne Rowe
Summary: This paper proposes a novel load balancing methodology based on UE-SC association, considering the load of SCs in UE's neighborhood and the SINR/CQI parameters. System-level simulations show that the proposed algorithm provides a more balanced load and higher network throughput.
2022 IEEE ASIA PACIFIC CONFERENCE ON WIRELESS AND MOBILE (APWIMOB)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Imran Moez Khan, Shuai Sun, Wayne S. T. Rowe, Andrew Thompson, Akram Al-Hourani, Kandeepan Sithamparanathan
Summary: This paper investigates the use of smartphone sensors for detecting phone use cases. By comparing results from different classifiers, it is found that the onboard accelerometer provides the highest accuracy as a sensor modality, and neural network performs the best as a classifier. The paper also includes a discussion on the theoretical aspects of the classifiers.
2022 32ND INTERNATIONAL TELECOMMUNICATION NETWORKS AND APPLICATIONS CONFERENCE (ITNAC)
(2022)
Proceedings Paper
Telecommunications
Chiu Chun Chan, Basset Al Homssi, Akram Al-Hourani
Summary: This paper presents an analytic framework for modeling the uplink performance of IoT-over-Satellite networks, and compares the performance of random constellations with that of Walker constellations. The results show that random constellations provide more reliable and higher throughput performance.
IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)
(2022)
Article
Telecommunications
Bisma Manzoor, Bassel Al Homssi, Akram Al-Hourani
Summary: This paper evaluates the impact of transmission repetition on the coverage probability and energy cost of IoT links, and proposes two diversity combining techniques. The analytic framework provided can assist network designers in maximizing network coverage while minimizing device energy expenditure.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2022)
