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
Computer Science, Information Systems
Hongjiang Lei, Chen Zhu, Ki-Hong Park, Weijia Lei, Imran Shafique Ansari, Theodoros A. Tsiftsis
Summary: This article examines the secure communication performance of nonorthogonal multiple access (NOMA) communication systems with aerial eavesdroppers. It investigates the ground-to-ground and ground-to-air scenarios and derives exact expressions for the secrecy outage probability.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Addanki Prathima, Devendra Singh Gurjar, Suneel Yadav, Dragana Krstic, Nenad Milosevic, Jugoslav Jokovic
Summary: This article investigates the performance of UAV-assisted wireless power transfer-enabled communications for energy-constrained wireless devices. The study analyzes the system's outage probability, throughput, and energy efficiency by considering various fading and shadowing scenarios. The findings provide significant insights into the system's behavior.
IEEE SENSORS JOURNAL
(2022)
Article
Remote Sensing
Aleksandra Cvetkovic, Vesna Blagojevic, Jelena Manojlovic
Summary: This paper provides a performance analysis of an energy constrained IoT system with a UAV. The system uses a power beacon to supply energy to a sensor node without other power sources, and the UAV collects sensor data. The analysis considers a Nakagami-m fading environment and analyzes outage and capacity performances under the time-switching protocol. The impact of various system and channel parameters on system performances is demonstrated.
Article
Engineering, Electrical & Electronic
Conghui Hao, Yueyun Chen, Zhiyuan Mai, Guang Chen, Meijie Yang
Summary: This paper aims to further reduce UAV energy consumption while minimizing task completion time. A novel UAV utility function is proposed to describe task completion time and energy consumption. The problem is formulated as a mixed-integer nonconvex utility maximization problem, and a two-layer joint task time and trajectory optimization (JTTTO) iterative algorithm is proposed to solve it. The proposed data acquisition scheme successfully decreases UAV energy consumption while minimizing task completion time.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Na Lin, Yanbo Fan, Liang Zhao, Xiaoming Li, Mohsen Guizani
Summary: This paper proposes a global energy efficiency maximization strategy for multi-UAV enabled communication systems. The strategy optimizes the trajectory control of UAVs to maximize the global energy efficiency, taking into account both communication throughput and total energy consumption.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Yun Chen, Guoping Zhang, Hongbo Xu, Yinshuan Ren, Xue Chen, Ruijie Li
Summary: This paper investigates the power optimization problem of transmit nodes in NOMA-based D2D networks considering the estimation error of channel. By utilizing equivalent transformation and semi-definite relaxation algorithm, the thorny non-convex problem is efficiently solved. The results show that channel estimation error increases the power consumption and NOMA-based D2D systems outperform OMA.
Article
Telecommunications
Rambod Pakrooh, Ali Bohlooli
Summary: Unmanned Aerial Vehicles (UAVs) have been widely developed for military applications, and with the advancement of IoT and smart devices, they are now being used in various domains. The inherent advantages of UAVs, such as high dynamicity and low cost, have motivated researchers to integrate them into IoT systems. Future directions include addressing the challenges associated with designing UAV-assisted IoT systems.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Xiao-Hui Lin, Su-Zhi Bi, Nan Cheng, Ming-Jun Dai, Hui Wang
Summary: This article discusses how to use drones to collect ground data in IoT systems, and proposes an alpha-fairness approach to balance energy consumption among IoT sensors to improve system longevity. By designing an alpha-utility function to balance the tradeoff between energy efficiency and fairness, maximizing the utility function to optimize bandwidth allocation, transmission power, and UAV trajectory. The article also demonstrates how to properly set the alpha value according to specific application scenarios to achieve different levels of energy fairness.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Nan Cheng, Shen Wu, Xiucheng Wang, Zhisheng Yin, Changle Li, Wen Chen, Fangjiong Chen
Summary: With the rapid development of the Internet of Things (IoT), unmanned aerial vehicles (UAVs) are widely used to improve the performance of IoT networks. These UAVs can provide wireless access to IoT devices and perform various IoT services and applications. However, the complexity of UAV-assisted IoT networks has led to the use of artificial intelligence (AI)-based methods to optimize, schedule, and coordinate these networks. This article comprehensively analyzes the impact of AI on UAV-assisted IoT networks and discusses potential research directions.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Seyed Mostafa Bozorgi, Mehdi Golsorkhtabaramiri, Samaneh Yazdani, Sahar Adabi
Summary: The Internet of Things (IoT) is a platform for large-scale data collection in the socio-physical space. Wireless Sensor Nodes (WSN) and Unmanned Aerial Vehicles (UAVs) are crucial in reducing costs and improving usability. The Smart Optimizer Approach (SOA) is introduced to tackle energy consumption in UAV-Assisted IoT Wireless Networks. A new clustering protocol, SOAbased Clustering (SOAC), is proposed to address the limitations of traditional protocols in large-scale networks.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Ahmed A. Al-Habob, Octavia A. Dobre, Sami Muhaidat, H. Vincent Poor
Summary: This study addresses the problem of minimizing energy consumption by disseminating files to IoT devices using UAV technology. It proposes a framework for selecting optimal paths and utilizes ant colony optimization algorithm for efficient data dissemination, which outperforms the traditional hovering method.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Chemistry, Analytical
Lucas Rodrigues, Andre Riker, Maria Ribeiro, Cristiano Both, Filipe Sousa, Waldir Moreira, Kleber Cardoso, Antonio Oliveira-Jr
Summary: This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs) as data collectors for the Internet of Things (IoT). The proposed model addresses both single and multiple aircraft, as well as a clustering technique to extend the scope of IoT devices visited by UAVs. The flight plan focuses on preventing breakdowns due to a lack of battery charge and maximizing the number of nodes visited, with consideration of data storage limitations and energy consumption of drones. Simulation results show the algorithm's behavior in generating routes, and the model is evaluated using a reliability metric.
Article
Computer Science, Information Systems
Di Lin, Weiwei Wu
Summary: This article proposes a lightweight RF fingerprinting recognition method and a resource allocation scheme, taking into account the limited computing power and resources of UAVs, to ensure the security of UAV-based IoT.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Abhishek Mondal, Deepak Mishra, Ganesh Prasad, Ashraf Hossain
Summary: This article proposes an energy-efficient UAV-assisted IoT network, which reduces the energy consumption of all devices by optimizing the trajectory, device association, and power allocation of the UAV. Reinforcement learning is used to solve the complex optimization problem and a low complexity iterative algorithm is proposed. Numerical results validate the effectiveness of the proposed methodology.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Zhijie Su, Wanmei Feng, Jie Tang, Zhen Chen, Yuli Fu, Nan Zhao, Kai-Kit Wong
Summary: This article investigates the energy efficiency optimization problem for the Device-to-Device (D2D) communications underlaying unmanned aerial vehicles (UAVs)-assisted Industrial Internet of Things (IIoT) networks with simultaneous wireless information and power transfer (SWIPT). A joint UAV location and resource allocation algorithm is proposed to solve the nonconvex optimization problem involving the UAV's location, beam pattern, power control, and time scheduling. Numerical results demonstrate the significant energy efficiency gain achieved by the proposed algorithm.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Chao Wang, Xinying Chen, Jianping An, Zehui Xiong, Chengwen Xing, Nan Zhao, Dusit Niyato
Summary: In this paper, a covert communication scheme assisted by UAV-IRS is proposed to maximize the covert transmission rate and defend against adversarial eavesdropping. The ground transmitter secretly sends private messages to a legitimate receiver via the UAV-IRS to prevent detection by an adversary. The scheme optimizes the transmit power, IRS phase shift, and UAV-IRS location to meet covert requirements.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Xinying Chen, Nan Zhao, Zheng Chang, Timo Hamalainen, Xianbin Wang
Summary: In this paper, a secure UAV-aided data collection and transmission scheme is proposed to ensure the freshness and security of the transmission from the sensors to the remote ground base station. The trajectory, flight duration, and user scheduling are optimized to maximize energy efficiency during the data collection phase. In the UAV data transmission phase, the maximum rate of transmission is considered to achieve a maximum secrecy rate.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Wenjing Wei, Xiaowei Pang, Jie Tang, Nan Zhao, Xianbin Wang, Arumugam Nallanathan
Summary: In this paper, a secure aerial IRS-assisted transmission design in wireless networks is proposed, which combines UAV and IRS to establish desired virtual LoS links and ensure security. The system performance is optimized by maximizing the worst-case sum secrecy rate, and the optimization problem is solved using an alternating algorithm. Simulation results demonstrate the effectiveness of the proposed scheme and the improvement in security achieved through joint optimization.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Mingqian Liu, Hongyi Zhang, Zilong Liu, Nan Zhao
Summary: This article investigates the unique advantages and security risks of deep learning in spectrum sensing in cognitive radio-based Internet of Things networks. By combining traditional interference methods with data poisoning attacks, a new adversarial attack method is proposed to reduce sensing accuracy, while introducing a novel design of jamming waveform to enhance interference capability.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Electrical & Electronic
Liwen Zhang, Junyu Liu, Min Sheng, Nan Zhao, Jiandong Li
Summary: This paper aims to improve the downlink user sum rate in Satellite Integrated Terrestrial Network (SITN). A joint interference management and user association (JIMUA) scheme is proposed to enhance the backhaul capacity and meet the user demands by employing collaborative computing.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Yuqiao Tong, Dongdong Li, Zhutian Yang, Nan Zhao, Yunfei Chen, Yonghui Li
Summary: Combining rate splitting with cooperative relay can improve the sum rate of conventional RS networks. However, the challenge lies in preventing untrusted relays from eavesdropping on private messages. To address this, a two-slot CRS scheme is proposed to guarantee security of the far user. The problem is solved using an iterative algorithm. Simulation results show the scheme's effectiveness in preventing eavesdropping.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Renhao Zhang, Xuanheng Li, Nan Zhao
Summary: This paper proposes a joint power allocation and time splitting scheme to enable devices to implement both dynamic spectrum access (DSA) and simultaneously wireless information and power transfer (SWIPT) simultaneously, aiming to maximize long-term throughput while ensuring interference limitation and energy supply requirements.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Yuqiao Tong, Dongdong Li, Zhutian Yang, Zehui Xiong, Nan Zhao, Yonghui Li
Summary: Two RS schemes are proposed to improve the spectrum efficiency and degrees of freedom of multi-access transmissions by using different successive interference cancellation (SIC) layers. The users decode the common stream and then their own private streams according to the scheme. One scheme uses zero-forcing for interference cancellation, while the other adopts maximum ratio transmission for the trusted far user. Outage probability and secrecy outage probability are analyzed based on channel statistics and achievable rates. Simulation results verify the theoretical findings and demonstrate the advantages of the two schemes in terms of common stream transmission and the security for the far user.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Xuanheng Li, Sike Cheng, Haichuan Ding, Miao Pan, Nan Zhao
Summary: The emergence of the Internet of Things (IoT) has caused congestion in telecommunications networks. Unmanned aerial vehicles (UAVs) are considered a promising solution for relieving this congestion. By embedding cognitive radios into UAVs, idle spectrums can be utilized to build backhaul links. However, the success of offloading traffic through cognitive UAV (CUAV) assistance depends on both the traffic demand and spectrum environment. In this paper, we propose a deep reinforcement learning (DRL) based solution, DRL-(TB)-B-3, that jointly designs trajectory, time allocation, band selection, and transmission power control to maximize energy efficiency for CUAV-assisted traffic offloading. Simulation results demonstrate the effectiveness of our proposed strategy.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Wei Wang, Yang Cao, Min Sheng, Jie Tang, Nan Zhao, Dusit Niyato, Kai-Kit Wong
Summary: Due to the increasing demand for higher spectrum efficiency and large-scale connectivity, non-orthogonal multiple access (NOMA) has become a highly competitive candidate for the upcoming sixth-generation (6G) systems. However, the unstable wireless propagation environment and potential wireless security risk hinder the applications of NOMA. Fortunately, the intelligent reflecting surface (IRS) that can construct three-dimensional beamforming and reconfigure channels has emerged as an efficient technology to overcome the limitations of NOMA. In this article, an overview of NOMA is presented, along with its main shortcomings and security risks. The IRS technology is then introduced, highlighting its enhancement in NOMA networks. The article also addresses typical security threats in IRS-NOMA networks and proposes countermeasures based on joint transmit beamforming and IRS reflecting beamforming to combat external and internal eavesdropping.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Xinying Chen, Jianping An, Zehui Xiong, Chengwen Xing, Nan Zhao, F. Richard Yu, Arumugam Nallanathan
Summary: Information security is a critical issue in wireless networks, and covert communication emerges as a potential solution due to its high-security level. By hiding transmitted signals in noise, covert communication can ensure stronger information security. However, challenges such as effective randomness utilization and low signal-to-interference-plus-noise ratio still exist in its practical implementation.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Article
Engineering, Civil
Mingqian Liu, Zhenju Zhang, Yunfei Chen, Jianhua Ge, Nan Zhao
Summary: The air transportation communication jamming recognition model based on deep learning (DL) can identify and classify communication jamming quickly and accurately, improving the safety and reliability of air traffic. However, the vulnerability of deep learning makes the model susceptible to carefully designed adversarial examples. This study proposes a double level attack method to improve defense performance and transfer the knowledge from the model to jamming recognition models in other wireless communication environments through transfer learning.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Dongdong Li, Zhutian Yang, Nan Zhao, Yunfei Chen, Zhilu Wu, Yonghui Li
Summary: To handle the security problem of cognitive radio (CR) systems, secondary users (SUs) can assist the primary user (PU) in secure transmission. The rate-splitting multiple access (RSMA) is adopted for spectrum sharing among CR users, with nonorthogonal multiple access (NOMA) and space division multiple access (SDMA) as special cases. A unified rate-splitting framework is established in this article to ensure secure spectrum sharing without knowledge of wiretap channels. The framework allows for effective transmission of common stream and secure transmission of private stream for both PU and SU, and can also enhance security in NOMA and SDMA through precoding design.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yu Ding, Yunqi Feng, Weidang Lu, Shilian Zheng, Nan Zhao, Limin Meng, Arumugam Nallanathan, Xiaoniu Yang
Summary: In this paper, a novel online edge learning offloading (OELO) scheme is proposed for UAV-assisted MEC secure communications, which improves secure computation performance. By optimizing binary offloading decision and resource management, while ensuring dynamic task data queue stability and minimum secure computing requirement, the secure computation efficiency is maximized. The Dinkelbach method is used to transform the optimization problem into a tractable form, and the offloading decision is generated based on deep reinforcement learning (DRL) and resource management is optimized iteratively through successive convex approximation (SCA). Simulation results show that the proposed scheme achieves better computing performance, stability, and security compared to benchmarks.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2023)
