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Resource Allocation for Throughput Maximization in Cognitive Radio network with NOMA

computers, Materials & Continua 2022年第1期70卷 195-212页

作者： Xiaoli He Yu Song Yu Xue Muhammad Owais Weijian Yang Xinwen Cheng School of Computer Science Sichuan University of Science and EngineeringZigong643000China Department of Network Information Management Center Sichuan University of Science and EngineeringZigong643000China School of Information Engineering South West University of Science and TechnologyMianyang621010China School of Computer and Software Nanjing University of Information Science and TechnologyJiangsu210044China Alhamd Islamic University Airport Road Quetta BalochistanPakistan

Spectrum resources are the precious and limited natural *** order to improve the utilization of spectrum resources and maximize the network throughput,this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonalmultiple access(CRN-NOMA).NOMA,as the key technology of the fifth-generation communication(5G),can effectively increase the capacity of 5G *** optimization problem proposed in this paper aims to maximize the number of secondary users(SUs)accessing the system and the total throughput in the *** the constraints of total power,minimum rate,interference and SINR,CRN-NOMA throughput is maximized by allocating optimal transmission ***,for the situation of multiple sub-users,an adaptive optimization method is proposed to reduce the complexity of the optimization ***,for the optimization problem of nonlinear programming,a maximization throughput optimization algorithm based on Chebyshev and convex(MTCC)for CRN-NOMA is proposed,which converts multi-objective optimization problem into single-objective optimization problem to *** the same time,the convergence and time complexity of the algorithm are *** analysis and simulation results show that the algorithm can effectively improve the system *** terms of interference and throughput,the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access(OFDMA).This paper provides important insights for the research and application of NOMA in future communications.

关键词： Resource allocation non-orthogonal multiple access cognitive radio network throughput maximization Chebyshev convex

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A Compositional Resilience Index for Computationally Efficient Safety Analysis of Interconnected Systems 62

A Compositional Resilience Index for Computationally Efficie...

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62nd IEEE Conference on Decision and Control, CDC 2023

作者： Niu, Luyao Maruf, Abdullah Al Clark, Andrew Mertoguno, J. Sukarno Poovendran, Radha University of Washington Network Security Lab Department of Electrical and Computer Engineering SeattleWA98195-2500 United States California State University Department of Electrical and Computer Engineering Los AngelesCA90032 United States McKelvey School of Engineering Washington University in St. Louis Electrical and Systems Engineering Department St. LouisMO63130 United States School of Cybersecurity and Privacy Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (纸本)9798350301243

Interconnected systems such as power systems and chemical processes are often required to satisfy safety properties in the presence of faults and attacks. Verifying safety of these systems, however, is computationally challenging due to nonlinear dynamics, high dimensionality, and combinatorial number of possible faults and attacks that can be incurred by the subsystems interconnected within the network. In this paper, we develop a compositional resilience index to verify safety properties of interconnected systems under faults and attacks. The resilience index is a tuple serving the following two purposes. First, it quantifies how a safety property is impacted when a subsystem is compromised by faults and attacks. Second, the resilience index characterizes the needed behavior of a subsystem during normal operations to ensure safety violations will not occur when future adverse events occur. We develop a set of sufficient conditions on the dynamics of each subsystem to satisfy its safety constraint, and leverage these conditions to formulate an optimization program to compute the resilience index. When multiple subsystems are interconnected and their resilience indices are given, we show that the safety constraints of the interconnected system can be efficiently verified by solving a system of linear inequalities. We demonstrate our developed resilience index using a numerical case study on chemical reactors connected in series. © 2023 IEEE.

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UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Communications Based on DRL 100

UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Commu...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Hu, Jiawei Ju, Ying Wang, Haoyu Liu, Lei Pei, Qingqi Shee, Y.G. Zhu, Xiaojie Wu, Celimuge University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States Xidian University Guangzhou Institute of Technology Guangzhou510555 China Xi'an University of Posts Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China Universiti Tunku Abdul Rahman Department of Electrical and Electronic Engineering Kajang43000 Malaysia King Abdullah University of Science and Technology Department of Computer Electrical and Mathematical Sciences and Engineering Thuwal239556900 Saudi Arabia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan

ISBN: (纸本)9798331517786

Ensuring reliable communication can be incredibly challenging in emergencies due to the breakdown of conventional infrastructure. However, a promising solution is on the horizon: the integration of reconfigurable intelligent surfaces (RIS) onto unmanned aerial vehicles (UAV), known as UAV-RIS. This innovative approach holds the potential to offer agile and adaptable communication services during crises, overcoming the limitations of traditional systems. This paper establishes an innovative UAV-RIS system with an active RIS to enhance the uplink communication between ground devices (GDs) and the air base station (ABS). We present an advanced communication strategy utilizing deep reinforcement learning (DRL) for UAV-RIS-supported uplink communication in dynamic emergencies. This scheme is designed to optimize the energy efficiency of the UAV-RIS communication system while adhering to quality of service (QoS) constraints for all GDs. It achieves this by jointly optimizing the trajectory of the UAV-RIS and the phase of the active RIS, ensuring efficient and reliable communication in challenging environments. To optimize the performance of the system, we propose a hierarchical Proximal Policy Optimization (H-PPO) algorithm and the upper and lower layers of H-PPO optimize the trajectory and phase control, respectively. Simulation results demonstrate that our scheme can effectively learn the communication strategy to enhance the performance of dynamic emergency communication networks. © 2024 IEEE.

关键词： active reconfigurable intelligent surface deep reinforcement learning quality of service UAV trajectory

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Enhancing Efficiency and Empowering Institutions: Leveraging Wireless Sensor Devices, IoT Edge Computing, and Fog Computing in Educational Systems 7

Enhancing Efficiency and Empowering Institutions: Leveraging...

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7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023

作者： Siddiqui, Shams Tabrez Ali Sohail, Md Mohammed Aftab, Aasif Sarfaraz, Mohd Alam, Mohammad Imran Salim, Abu College of Cs It Jazan University Department of Computer Science Jazan Saudi Arabia College of Cs It Jazan University Department of Computer & Network Engineering Jazan Saudi Arabia College of Cs It Jazan University Department of Information Technology and Security Jazan Saudi Arabia

ISBN: (纸本)9798350343144

Wireless sensor devices, edge computing, and fog computing can transform education by improving efficiency and empowering institutions. This research paper explores the application of these technologies in educational settings and investigates their benefits, challenges, and potential solutions. Educational institutions can track classroom occupancy, ambient conditions, and student participation using wireless sensor systems. loT edge computing allows data processing and analysis at the network edge for rapid insights and decision-making. Fog computing integrates cloud resources with edge computing to support complicated computations and data storage. Wireless sensor devices, loT edge computing, and fog computing are used to optimize educational processes like resource management, student tracking, personalized learning, and campus security. Data privacy, security, scalability, and interoperability issues are studied and solutions suggested. This research shows how wireless sensor devices, loT edge computing, and fog computing may alter educational systems, helping institutions improve efficiency and empower stakeholders. © 2023 IEEE.

关键词： Fog computing

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SaTrack: LoS/NLoS State-Aware WiFi Indoor Tracking System 21

SaTrack: LoS/NLoS State-Aware WiFi Indoor Tracking System

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21st Annual IEEE International Conference on Sensing, Communication, and networking, SECON 2024

作者： Zhou, Yinnan Zhou, Hao Li, Luowei Chen, Siming Liu, Zhi Li, Xiang-Yang LINKE Lab School of Computer Science and Technology University of Science and Technology of China China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China China Department of Computer and Network Engineering The University of Electro-Communications Tokyo182-8585 Japan

ISBN: (纸本)9798331519186

WiFi-based technology is appealing for indoor localization due to the widely deployed infrastructures. Recently, path separation solutions have been proposed to address the multipath effects and achieve decimeter-level localization accuracy in line-of-sight (LoS) scenarios. However, these solutions experience serious performance degradation in non-line-of-sight (NLoS) scenarios, and couldn’t be used for mobile device tracking where continuous LoS/NLoS switching happens. In this paper, we propose SaTrack, a LoS/NLoS state-aware mobile device tracking system. SaTrack identifies LoS/NLoS states based on the diversity of the strongest estimated paths when using different reference antennas. With the observation of spatial aggregation and temporal continuity for the Tx-Rx direct path, SaTrack chooses the direct path through two-step clustering, i.e., clustering in the spatial domain to form candidates and clustering again in the temporal domain to select the winner. Extensive experiments are conducted to evaluate the effectiveness of SaTrack. In a typical indoor environment with abundant multipath, SaTrack achieves 0.64m and 1.27m for the median and 90th percentile tracking errors, outperforming the state-of-the-art (SOTA) solutions. © 2024 IEEE.

关键词： Wi-Fi

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Design and Simulation of a 3-Transistor Active Pixel Sensor Using MATLAB Simulink 23

Design and Simulation of a 3-Transistor Active Pixel Sensor ...

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23rd International Arab Conference on Information Technology, ACIT 2022

作者： Al Tarabsheh, Anas Alheeh, Huda Abu Dhabi University Department of Electrical Biomedical Computer Engineering Abu Dhabi United Arab Emirates The Hashemite University Faculty of Engineering Electrical Engineering Department Jordan Al Ain University Department of Network and Communication Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350320244

This paper proposes a Simulink model to simulate the pixel circuit with variable light intensities to investigate the impact of the light intensity on the CMOS image sensor pixels. This article also explores the CMOS image sensor pixel categories and presents the design and the simulation of the 3- Transistor (3T) Active Pixel Sensor (APS) in the MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single-pixel sensing circuit which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for pixel operation;reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including the dark case, is simulated, and it is shown its inverse proportionality with the light intensity. As a result, the Cpd discharges faster if the amount of light is increased. The more the light intensity, the lower value for the output voltage. © 2022 IEEE.

关键词： Photodiodes

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Conceptual Design of Wireless Smart Grid for the Optimization of Electric Transmission in Iraq 3

Conceptual Design of Wireless Smart Grid for the Optimizatio...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Abbas, Aeshah Burhan Almohammedi, Akram A. Balfaqih, Mohammed Darshi, Sam Karabük University Electrical & Electronics Engineering Department Karabük Turkey Karabük University Electrical & Electronics Department Karabük Turkey South Ural State University Automobile Transportation Department Chelyabinsk Russia University of Jeddah Department of Computer and Network Engineering Jeddah23218 Saudi Arabia Indian Institute of Technology Ropar Department of Electrical Engineering Punjab India

ISBN: (纸本)9798350321487

Rapid development of technology has resulted in a considerable increase in electricity consumption, which has created a barrier not only because of the generation but also in delivery. Thus, when demand increases, the complexity of the electrical network increases as a result of the increased need for improved dependability, efficiency, protection, energy, and environmental sustainability. According to the world bank statistics, Iraq's loss was 51% during distribution, and it is considered significantly high. This study proposes a wireless network-based design for detecting and optimizing Iraq's electricity distribution infrastructure. Moreover, the suggested module is composed of several data gathering methods that are required for the various paths of the power distribution systems. This design offers viable support for a variety of issues confronting Iraq's power distribution systems, including variable voltage levels caused by fluctuating electrical usage, power burglary, manual invoicing, and transmission line breakdowns. The suggested design is intended for use with single-phase power transmission systems;however, it may be adapted for use with three-phase power distribution systems with slight improvements. The introduction of this method will result in significant energy savings, allowing for the availability of electricity to a greater number of users than previously possible in a crowded place. The suggested smart grid design, which was created for the Iraq context, permits real-time control of energy consumption, optimal electricity consumption, minimal loss, diagnosis of power failures, breakdowns, and automatic invoicing. © 2023 IEEE.

关键词： Electric power transmission

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Inverse Scattering of Two-dimensional Circular Cylindrical Conductors by Convolutional Neural network

Inverse Scattering of Two-dimensional Circular Cylindrical C...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Po-Hsiang Chen Hsiu-Hui Hsu Chien-Ching Chiu Wei Chien Kai-Xu Yu Department of Electrical and Computer Engineering Tamkang University New Taipei City Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

We used a Convolutional Neural network (CNN) to reconstruct the electromagnetic imaging of a perfect conductor in half-space through the traverse magnetic wave. Since the conventional iterative algorithm is time-consuming, we developed a real-time electromagnetic imaging technique to apply to the CNN to reconstruct the half-space conducting cylinders. The sizes and positions of the cylinders were calculated through the Direct Sampling Method (DSM) in the scattered field. The original ground truth was fed to CNN for training to predict accurate sizes and positions of the shape. The accurate size and position of the shape for the perfect conductor were reconstructed.

关键词： Magnetic field measurement Accuracy Shape Magnetic resonance imaging Two-dimensional displays Conductors Sampling methods

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Biometric-Based Access Control Systems with Robust Facial Recognition in IoT Environments 3

Biometric-Based Access Control Systems with Robust Facial Re...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Satish Babu, B.V. Manoranjini, J. Changala, Ravindra Aarif, Mohd Mary, S. Suma Christal Raj, I Infant Prasad v Potluri Siddhartha Institute of Technology Department of It Vijayawada India Chaitanya Bharathi Institute of Technology Department of Ai & Ml Hyderabad India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India Associate Editor-Publishing Global Research Network Noida India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India

ISBN: (纸本)9798350361186

The integration of biometric-based access control systems with robust facial recognition technology within Internet of Things (IoT) environments holds paramount significance in addressing contemporary security challenges. The novelty of the research endeavours to contribute to this critical area by investigating and implementing a novel approach, employing Convolutional Neural networks (CNN) for facial classification within the biometric framework. The significance of this study lies in its potential to enhance security measures in IoT environments, ensuring reliable and efficient access control. Previous attempts at integrating facial recognition into IoT have encountered notable challenges, including suboptimal accuracy, vulnerability to adversarial attacks, and scalability issues. This research builds upon these prior issues by introducing CNN for facial classification, leveraging its capabilities in image processing and pattern recognition to achieve enhanced accuracy and resilience against potential security threats. The novelty of the study is underscored by the application of CNN within the biometric context of IoT, offering a cutting-edge solution tailored to the intricacies of interconnected devices. Experiments conducted on benchmark datasets showcase the promising capabilities of the proposed system, with face recognition accuracies reaching an impressive 98%. These results underscore the potential of this research to significantly advance the state-of-the-art in biometric-based access control, particularly within the context of IoT environments. The utilization of CNN introduces a pioneering element, contributing to the evolution of secure and efficient access control solutions in the era of IoT. © 2024 IEEE.

关键词： Biometrics

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Evaluating Recent 2D Human Pose Estimators for 2D-3D Pose Lifting

Evaluating Recent 2D Human Pose Estimators for 2D-3D Pose Li...

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International Conference on Automatic Face and Gesture Recognition

作者： Soroush Mehraban Yiqian Qin Babak Taati KITE Research Institute University Health Network Institute of Biomedical Engineering University of Toronto Department of Electrical and Computer Engineering University of Toronto Department of Computer Science University of Toronto

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

Monocular 3D human pose estimation involves predicting the 3D pixel coordinates of key body joints from a 2D image or video. Typically, a 2D estimation model is employed to initially determine joint locations in an image, followed by training a separate model to lift these positions to 3D coordinates. In this paper, we evaluate the performance of recently proposed 2D human pose estimation models as different inputs for training and evaluation of 2D-3D lifting models. In addition, we propose four simple merging strategies to combine the outputs of these 2D human pose estimators and generate less noisy 2D inputs. To evaluate, four recent 2D pose estimators—ViTPose, PCT, MogaNet, and TransPose—are selected, and their corresponding 2D outputs are generated on the Human3.6M dataset. Subsequently, MotionAGFormer and PoseFormerV2 are trained and evaluated using each created 2D input and its corresponding 3D motion-capture ground truth. ViTPose stands out as the top-performing 2D estimator, and employing all merging strategies proves beneficial in generating a less noisy 2D input. Code and data are available at https://***/TaatiTeam/2DEstimatorEval.

关键词： Training Solid modeling Three-dimensional displays Codes Face recognition Merging Pose estimation

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