Baofeng Ji^1,2,3,*, Ying Wang^1,2,3, Weixing Wang¹, Shahid Mumtaz⁴, Charalampos Tsimenidis⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1885-1905, 2024, DOI:10.32604/cmes.2023.030872

Abstract The utilization of mobile edge computing (MEC) for unmanned aerial vehicle (UAV) communication presents a viable solution for achieving high reliability and low latency communication. This study explores the potential of employing intelligent reflective surfaces (IRS) and UAVs as relay nodes to efficiently offload user computing tasks to the MEC server system model. Specifically, the user node accesses the primary user spectrum, while adhering to the constraint of satisfying the primary user peak interference power. Furthermore, the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes, namely time switching (TS) and power splitting… More >

Ying Zhang¹, Weiming Niu², Supu Xiu^1,3, Guangchen Mu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1865-1884, 2024, DOI:10.32604/cmes.2023.030114

Abstract In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first propose the successive convex approximation… More >

Ying Zhang^1,*, Weiming Niu², Leibing Yan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 885-902, 2024, DOI:10.32604/cmes.2023.029234

Abstract In this paper, we consider mobile edge computing (MEC) networks against proactive eavesdropping. To maximize the transmission rate, IRS assisted UAV communications are applied. We take the joint design of the trajectory of UAV, the transmitting beamforming of users, and the phase shift matrix of IRS. The original problem is strong non-convex and difficult to solve. We first propose two basic modes of the proactive eavesdropper, and obtain the closed-form solution for the boundary conditions of the two modes. Then we transform the original problem into an equivalent one and propose an alternating optimization (AO) based method to obtain a… More >

Hui Wei, Leibing Yan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1805-1824, 2023, DOI:10.32604/cmes.2023.028072

Abstract This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communication. With the popularization of UAV technology, more and more communication scenarios need UAV support. We consider using IRS to improve the secrecy efficiency. Specifically, IRS and UAV trajectories work together to counter potential eavesdroppers, while balancing the secrecy rate and energy consumption. The original problem is difficult to solve due to the coupling of optimization variables. We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem, and then prove the equivalence between relaxation problem and the original… More >

Waleed Aldosari^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111

Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >

Fawad Salam Khan^1,4, Mohd Norzali Haji Mohd^1,*, Saiful Azrin B. M. Zulkifli², Ghulam E Mustafa Abro², Suhail Kazi³, Dur Muhammad Soomro¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5741-5759, 2022, DOI:10.32604/cmc.2022.024927

Abstract The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades. Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle (UAV) required maximum accuracy. In this paper, we designed a hybrid framework, which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures. The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient (DDPG) to receive the best reward and take… More >

Wei Chen¹, Mi Liu^1,*, Xuhong Zhou², Jiandong Pan³, Haozhi Tan⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3159-3174, 2022, DOI:10.32604/cmc.2022.026664

Abstract In construction, it is important to check whether workers wear safety helmets in real time. We proposed using an unmanned aerial vehicle (UAV) to monitor construction workers in real time. As the small target of aerial photography poses challenges to safety-helmet-wearing detection, we proposed an improved YOLOv4 model to detect the helmet-wearing condition in aerial photography: (1) By increasing the dimension of the effective feature layer of the backbone network, the model's receptive field is reduced, and the utilization rate of fine-grained features is improved. (2) By introducing the cross stage partial (CSP) structure into path aggregation network (PANet), the… More >

Olubukola D. Adekola^1,*, Onyedikachi Kenny Udekwu², Oluwatobi Tolulope Saliu², Damilola Williams Dada², Stephen O. Maitanmi¹, Victor Odumuyiwa³, Olujimi Alao², Monday Eze², Funmilayo Abibat Kasali⁴, Ayokunle Omotunde²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 875-890, 2022, DOI:10.32604/csse.2022.021029

Abstract The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies primarily due to the lack… More >

Liu Duo-Neng^1,2, Hou Zhong-Xi¹, Guo Zheng¹, Yang Xi-Xiang¹, Gao Xian-Zhong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.6, pp. 531-565, 2016, DOI:10.3970/cmes.2016.111.531

Abstract Dynamic soaring is a flight maneuver to exploit gradient wind field to extend endurance and traveling distance. Optimal trajectories for permissible wind conditions are generated for loitering dynamic soaring as well as for traveling patterns with a small unmanned aerial vehicle. The efficient direct collection approach based on the Runge-Kutta integrator is used to solve the optimization problem. The fast convergence of the optimization process leads to the potential for real-time applications. Based on the results of trajectory optimizations, the general permissible wind conditions which involve the allowable power law exponents and feasible reference wind strengths supporting dynamic soaring are… More >