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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Khan, Muhammad Fawad Mei, Haoran Rahim, Shahnila Peng, Limei Ho, Pin-Han School of Computer Science and Engineering Kyungpook National University Deagu Korea Republic of University of Waterloo Department of Electrical and Computer Engineering WaterlooON Canada

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

This paper proposes using multiple reconfigurable intelligent surfaces (RISs) in SISO communications, considering that RISs can flexibly extend the wireless communication range. In a given area with multiple RISs, we propose an algorithm to select the optimal locations from a set of candidate points to deploy the RISs, aiming to maximize the achievable data rate. We investigate the impact of single-hop and multi-hops communication on the achievable data rate for the proposed algorithm and the results show that the deployment height and number of communication hops significantly affect the achievable data rate. © 2022 IEEE.

关键词： Wireless communication Spread spectrum communication Reconfigurable intelligent surfaces SISO communication

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Attacking Memristor-Mapped Graph Neural Network by Inducing Slow-to-Write Errors

Attacking Memristor-Mapped Graph Neural Network by Inducing ...

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IEEE European Test Symposium (ETS)

作者： Ching-Yuan Chen Biresh Kumar Joardar Janardhan Rao Doppa Partha Pratim Pande Krishnendu Chakrabarty Department of Electrical and Computer Engineering Duke University Department of Electrical and Computer Engineering University of Houston School of Electrical Engineering and Computer Science Washington State University School of Electrical Computer and Energy Engineering Arizona State University

Graph neural networks (GNNs) are becoming popular in various real-world applications. However, hardware-level security is a concern when GNN models are mapped to emerging neuromorphic technologies such as memristor-based crossbars. These security issues can lead to malfunction of memristor-mapped GNNs. We identify a vulnerability of memristor-mapped GNNs and propose an attack mechanism based on the identified vulnerability. The proposed attack tampers memristor-mapped graph-structured data of a GNN by injecting adversarial edges to the graph and inducing slow-to-write errors in crossbars. We show that 10% adversarial edge injection induces 1.11× longer write latency, eventually leading to a 44.33% error in node classification. Experimental results for the proposed attack also show that there is a 5.72× increase in the success rate compared to a software-based baseline.

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Toward Tight Lower Bounds for the Number of AC Optimal Power Flow Solutions

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IEEE Transactions on Control of Network Systems 2025年

作者： Tian, Wei Chiang, Hsiao-Dong Wang, Tao Tianjin University School of Electrical and Information Engineering Tianjin300072 China Cornell University Department of Electrical and Computer Engineering IthacaNY14853 United States Sun Yat-sen University School of Computer Science and Engineering Guangdong Guangzhou510006 China

Tight lower bounds on the number of locally optimal solutions provide useful information regarding the number of locally optimal solutions in the AC optimal power flow (ACOPF) problems. This paper is devoted to deriving three lower bounds for the number of locally optimal solutions by exploring feasible components of the OPF models and the associated Karush-Kuhn-Tucker (KKT) saddle points. The three lower bounds derived in this paper are shown to be progressively tightened by exploring the KKT saddle points. Each derived lower bound is equipped with a theoretical foundation. The analytical results of the derived lower bounds are illustrated on numerous IEEE test systems. © 2014 IEEE.

关键词： Load flow optimization

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Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-Level Sparsity via Mixture-of-Experts

Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Arc...

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IEEE International Conference on computer-Aided Design

作者： Rishov Sarkar Hanxue Liang Zhiwen Fan Zhangyang Wang Cong Hao School of Electrical and Computer Engineering Georgia Institute of Technology School of Electrical and Computer Engineering University of Texas at Austin

The computer vision community is embracing two promising learning paradigms: the Vision Transformer (ViT) and Multi-task Learning (MTL). ViT models show extraordinary performance over traditional convolution networks but are commonly recognized as computation-intensive, especially the self-attention with quadratic complexity. MTL uses one model to infer multiple tasks with better performance by enforcing shared representation among tasks, but a huge drawback is that, most MTL regimes require activation of the entire model even when only one or a few tasks are needed, causing significant computing waste. M 3 ViT is the latest multi-task Vi $T$ model that introduces mixture-of-experts (MoE), where only a small portion of subnetworks (“experts”) are sparsely and dynamically activated based on the current task. M 3 Vi $T$ achieves better accuracy and over 80% computation reduction and paves the way for efficient real-time MTL using ViT. Despite the algorithmic advantages of MTL, ViT, and even M 3 ViT, there are still many challenges for efficient deployment on FPGA. For instance, in general Transformer/ViT models, the self-attention is known as computational intensive and requires high bandwidth. In addition, softmax operations and the activation function GELU are extensively used, which unfortunately can consume more than half of the entire FPGA resource (LUTs). In the M 3 ViT model, the promising MoE mechanism for multi-task exposes new challenges for memory access overhead and also increases resource usage because of more layer types. To address these challenges in both general Transformer/ViT models and the state-of-the-art multi-task M 3 ViT with MoE, we propose Edge-MoE, the first end-to-end FPGA accelerator for multi-task ViT with a rich collection of architectural innovations. First, for general Transformer/ViT models, we propose (1) a novel reordering mechanism for self-attention, which reduces the bandwidth requirement from proportional to constant regardl

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A Survey on Semantic Communication Networks: Architecture, Security, and Privacy

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IEEE Communications Surveys and Tutorials 2024年

作者： Guo, Shaolong Wang, Yuntao Zhang, Ning Su, Zhou Luan, Tom H. Tian, Zhiyi Shen, Xuemin Xi'An Jiaotong University School of Cyber Science and Engineering Xi'an China University of Windsor Department of Electrical and Computer Engineering Windsor Canada University of Technology Sydney School of Computer Science Sydney Australia University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada

With the rapid advancement and deployment of intelligent agents and artificial general intelligence (AGI), a fundamental challenge for future networks is enabling efficient communications among agents. Unlike traditional human-centric, data-driven communication networks, the primary goal of agent-based communication is to facilitate coordination among agents. Therefore, task comprehension and collaboration become the key objectives of communications, rather than data synchronization. Semantic communication (SemCom) aims to align information and knowledge among agents to expedite task comprehension. While significant research has been conducted on SemCom for two-agent systems, the development of semantic communication networks (SemComNet) for multi-agent systems remains largely unexplored. In this paper, we provide a comprehensive and up-to-date survey of SemComNet, focusing on their fundamentals, security, and privacy aspects. We introduce a novel three-layer architecture for multi-agent interaction, comprising the control layer, semantic transmission layer, and cognitive sensing layer. We explore working modes and enabling technologies, and present a taxonomy of security and privacy threats, along with state-of-the-art defense mechanisms. Finally, we outline future research directions, paving the way toward intelligent, robust, and energy-efficient SemComNet. This survey represents the first comprehensive analysis of SemComNet, offering detailed insights into its core principles as well as associated security and privacy challenges. © 2024 IEEE.

关键词： Differential privacy

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Body Fat Prediction using Various Regression Techniques 2

Body Fat Prediction using Various Regression Techniques

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Mahesh, Nikhil Pati, Peeta Basa Deepa, K. Yanan, Suresh Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India University of Technology and Applied Sciences-Al Musannah Sultanate of Oman Department of Engineering Oman

ISBN: (纸本)9798350315905

Predicting body fat percentage is essential for addressing the obesity problem. This paper compares the performance of several machine learning models based on Regression, to predict the body fat percentage. Using a dataset of 252 participants with information on age, weight, height, and fat percentage, the models were assessed based on multiple performance criteria, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Squared Error(MSE). The results demonstrates that Random Forest Regressor surpass other models with a lower RMSE of 0.276. These findings suggest that machine learning models can be a valuable tool for precise BFP, the use of machine learning provides a faster and more precise method for predicting body fat percentage. Overall, the study's results suggest that machine learning models can be valuable tool for accurate body fat percentage prediction. © 2023 IEEE.

关键词： Forecasting

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IoT based Smart U-Turn Vehicle Accident Prevention System 2

IoT based Smart U-Turn Vehicle Accident Prevention System

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2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Pradeepkumar, G. Praveen Santhoshkumar, G. Rohith Bhat, C. Jeyalakshmi, M. Muthukumar, T. Kumar, Neelam Sanjeev Kpr Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India Nandha Engineering College Department of Electronics and Communication Engineering Tamilnadu Erode India Saveetha School of Engineering Simats Department of Computer Science and Engineering Chennai India Ssm Institute of Engineering and Technology Department of Electronics and Communication Engineering Dindigul India Kongunadu College of Engineering and Technology Department of Electrical and Electronics Engineering India Saveetha School of Engineering Simats Department of Biomedical Engineering Chennai India

ISBN: (纸本)9781665491990

Unintentional deaths occur at a very high rate in developing countries. Curved roads have significantly more fatalities than straight roads. This occurs mainly on U-turns, hairnin turns, and narrow mountain roads. Drivers in this position cannot see the vehicle approaching from the opposite direction. As a result, thousands of people are killed in car accidents every year. The best way to avoid further accidents is to alert the car driver approaching from the side. Place the ultrasonic range detection sensor on one side of the road before the bend and the light indicator system on the opposite side after the bend. When a vehicle approaches from afar, an ultrasonic sensor on one side of the road sends a signal to the other side of the road via a light system. In response to a warning, the driver may stop the car until the other vehicle has passed. A buzzer will also be used to warn the driver of the car that is approaching. © 2023 IEEE.

关键词： Ultrasonic applications

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Wavelength-multiplexed orbital angular momentum meta-holography

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PhotoniX 2024年第1期5卷 276-289页

作者： Jaehyuck Jang Seong-Won Moon Joohoon Kim Jungho Mun Stefan A.Maier Haoran Ren Junsuk Rho Department of Chemical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Department of Materials Science and Engineering Stanford UniversityStanfordCA 94305USA Department of Mechanical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907USA School of Physics and Astronomy Monash UniversityMelbourneVIC 3800Australia Department of Physics Imperial College LondonLondon SW72AZUK Department of Electrical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics Pohang 37673Republic of Korea National Institute of Nanomaterials Technology(NINT) Pohang 37673Republic of Korea

The field of high-bandwidth holography has been extensively studied over the past *** angular momentum(OAM)holography,which utilizes vortex beams with theoretically unbounded OAM modes as information carriers,showcases the large capacitance of hologram ***,OAM holography has been limited to a single wavelength,restricting its potential for full-color holography and *** this study,we propose wavelength and OAM multiplexed holography that utilizes the multiple dimensions of light—wavelength and OAM—to provide a multi-color platform that expands the information capacity of holographic storage *** proposed wavelength-OAM multiplexed holography is physically realized by a metasurface,the state-of-the-art optical element consisting of an array of artificially engineered *** silicon meta-atoms,the constituents of the metasurface,are engineered to possess wavelength selectivity by tailoring the dispersion of polarization *** meta-atoms are used to encode the calculated OAM-preserved phase maps based on our *** sampling grid of the phase map is rotated by 45°,which effectively suppress higher-order diffraction,providing a great strategy for achieving large field-of-view(FOV)*** successfully demonstrate six holographic images that are selectively reconstructed under the illumination of light with specific wavelengths(λ=450,635 nm)and topological charges(l=-2,0,2),without high-order *** work suggests that ultrathin meta-holograms can potentially realize ultrahigh-bandwidth full-color holography and holographic video displays with large FOV.

关键词： Metasurface Meta-holography Wavelength-multiplexed holography OAM holography

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Highly Directive Compact Multiband MIMO Antenna with Improved Gain for 5G Wireless Communication System 12

Highly Directive Compact Multiband MIMO Antenna with Improve...

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12th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2023

作者： Khan, Owais Khan, Shahid Alibakhshikenari, Mohammad Anab, Muhammad Nasir, Jamal Dalarsson, Mariana Cecos University of It and Emerging Sciences Peshawar Pakistan Comsats University Abbottabad Campus Department of Electrical and Computer Engineering Abbottabad Pakistan Universidad Carlos Iii de Madrid Department of Signal Theory and Communications Leganés Madrid28911 Spain Uet Peshawar Department of Electrical Engineering Pakistan Comsats University Islamabad Abbottabad Campus Department of Electrical and Computer Engineering Pakistan School of Electrical Engineering and Computer Science Kth Royal Institute of Technology SE Stockholm100-44 Sweden

ISBN: (纸本)9798350320602

A novel wide dual-band, Multiple-Input Multiple-Output (MIMO) antenna design for the upcoming fifth generation (5G) wireless communication is presented in this work. The size of single element of the proposed MIMO configuration is 4×5 mm2having L-shaped slot at the top edge. Rogers TMM4 with thickness of 0.508 mm having relative permittivity of 4.5 is used as a substrate material. Resonating frequencies of single antenna element are 40.15, 67.80 and 91.23 GHz with a wide impedance bandwidth of 2.22 and 34.43 GHz, respectively. The return loss at resonating frequencies are - 29.25, -66.30. and -20.00 dB with a good gain of 5.51, 4.27 and 3.70 dBi, respectively. The overall size of proposed 1×2 MIMO antenna is 4×7 mm2with a separation of 3.6 mm in between two elements and 0.6 mm separation between the edges and elements. The resonating frequencies of the proposed MIMO antenna are 40.36 GHz with reasonable gain of 4.62 dBi, and 67.59 and 95.73 GHz with improved gain of 5.42 and 5.70 dBi, respectively. The simulated return loss below -10db at resonating frequencies are -21.92, -63.38 and -27.87 dB, respectively. Inter-port isolation of above 20 dB throughout the operating frequencies, is achieved without using any complex technique. Envelope Correlation Coefficient (ECC) and Diversity Gain (DG), are important MIMO antenna parameters are less than 0.001 and 10 dB respectively. The proposed design with a high radiation efficiency at resonating frequencies is a good candidate for the satellite and radar communication as the achieved operating range lies in the proposed Ka-band (26-40 GHz), V-band (40-75 GHz), E-band (60-90 GHz) and W-band (75-110 GHz). © 2023 IEEE.

关键词： Microwave antennas

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Low Complexity Deep Learning Based Coordinated Beamforming for mmWave Massive MIMO Vehicular Networks

Low Complexity Deep Learning Based Coordinated Beamforming f...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Rekkas, Vasileios P. Sotiroudis, Sotirios P. Sarigiannids, Panagiotis Karagiannidis, George K. Christodoulou, Christos G. Goudos, Sotirios K. University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani Greece Aristotle University of Thessaloniki School of Electrical and Computer Engineering Thessaloniki Greece The University of New Mexico Department of Engineering and Computing United States Aristotle University of Thessaloniki ELEDIA@AUTH School of Physics Thessaloniki Greece Bharath University Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350318845

Enabling high mobility in millimeter-wave (mmWave) systems is crucial for next-generation wireless communication systems. Challenges arise in applications such as vehicular communications and wireless virtual/augmented reality. MmWave systems grapple with concerns related to narrow beams, signal vulnerability to obstructions that affect coverage, and the necessity for frequent handovers. Additionally, identifying optimal beamforming vectors in large antenna array mmWave systems involves substantial training overhead, impacting efficiency. This paper introduces a novel solution to address challenges in enabling high mobility in mmWave systems. The approach combines deep learning (DL) and coordinated beamforming to support applications such as vehicular communications and wireless virtual/augmented reality. The solution involves multiple coordinating base stations (BSs) serving a mobile user, utilizing a single pilot training sequence. A DL model predicts beamforming vectors based on received signals, providing reliable coverage, low latency, and minimal training overhead for highly mobile mmWave applications. Simulations demonstrate its effectiveness in high-mobility scenarios, approaching the performance of an optimal solution, a genie-aided solution that knows the optimal beamforming vectors without any training overhead. © 2024 IEEE.

关键词： Millimeter waves

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