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UAV-Enabled Image Capture and Wireless Delivery for On-Demand Surveillance Tasks

IEEE Transactions on Wireless communications 2024年第10期23卷 12995-13010页

作者： Van Cuong, Nguyen Hong, Y.-W. Peter Sheu, Jang-Ping National Tsing Hua University Institute of Communications Engineering the Department of Computer Science Hsinchu30013 Taiwan Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

This work examines the task assignment, transmission scheduling, and trajectory design of image-surveillance UAVs dispatched to serve on-demand image capture and delivery services to ground users, e.g., from drivers seeking images of traffic jams or security units requesting images of private homes. In each task, the UAVs are required to capture the image of a specified surveillance region and deliver the image to the requesting user before the deadline. The task assignment, transmission scheduling, and trajectory design are jointly determined to maximize the total surveillance area of the completed tasks. We first examine the single-UAV problem and propose an alternating optimization approach that adopts the exact penalty method to promote near-binary solutions and employ successive convex approximation to deal with the nonconvex trajectory optimization. Then, we extend to the multiple-UAV scenario where cross-UAV tasks may require images to be captured and delivered by different UAVs. To enable distributed implementation, we introduce auxiliary deadlines to limit the time available for local tasks and, thus, decouple the joint optimization problem into multiple single-UAV problems that can be solved in parallel following the procedure derived in the previous case. Numerical simulations are provided to demonstrate the effectiveness of the proposed solutions. © 2024 IEEE.

关键词： Trajectories

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AmplitudeArrow: On-the-Go AR Menu Selection Using Consecutive Simple Head Gestures and Amplitude Visualization

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IEEE Transactions on Visualization and computer Graphics 2025年第05期31卷 3408-3417页

作者： Tian, Yang Zhang, Youpeng Yan, Yukang Zhao, Shengdong Ma, Xiaojuan Shi, Yuanchun Guangxi University Department of Computer Science Guangxi Key Laboratory of Multimedia Communications and Network Technology China University of Rochester Department of Computer Science United States City University of Hong Kong School of Creative Media and the Department of Computer Science Hong Kong Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong Tsinghua University Department of Computer Science and Technology China

Heads-up computing aims to provide synergistic digital assistance that minimally interferes with users' on-the-go daily activities. Currently, the input modalities of heads-up computing are mainly voice and finger gestures. In this work, we propose and evaluate the AmplitudeArrow (AA) technique designed for on-the-go AR menu selection to demonstrate that consecutive simple head gestures can also be an effective input modality for heads-up computing. Specifically, AA arranges menu icons into one/two row(s). To select a target icon, the user first makes their head yaw to pre-select the target icon or the column containing it and then makes their head pitch to make the arrow in the target icon expand until the arrow covers the target icon completely, i.e., the pitch amplitude surpasses the selection confirmation threshold. User studies indicated that AA demonstrated robust resistance to walking-caused head perturbation and external factors such as other people/obstacles, delivering high accuracy (error rate © 1995-2012 IEEE.

关键词： Augmented reality

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Enhancing the Reliability of NR-V2X Sidelink Broadcast through Relay 29

Enhancing the Reliability of NR-V2X Sidelink Broadcast throu...

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29th IEEE Asia Pacific Conference on communications, APCC 2024

作者： Aoki, Shiro Tang, Suhua The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9798331517816

NR-V2X sidelink (SL) broadcast is used for the real-time exchange of position and other information between adjacent vehicles. However, its reliability degrades much in non-line-of-sight environments, where Blind ReTransmission (BReTX) does not work well. Relay can effectively address this issue, and a relaybased SL broadcast method was proposed in previous work. However, in this method, each vehicle must detect communication Link Quality (LQ) and exchange LQ Indicators (LQIs) with its neighbors to select a proper relay, which causes much overhead. This paper aims to improve the relay-based SL broadcast from two aspects. (i) To reduce the overhead, we suggest aggregating LQIs per direction, making the overhead of sharing LQIs irrelevant to the number of vehicles. (ii) To further improve reliability, we use an explicit ACK to deal with the potential failure of the transmission from the source vehicle to the relay. Using explicit ACKs allows the source vehicle to retransmit the packet until the relay vehicle correctly receives it, after which the relay vehicle handles the remaining retransmissions. Simulation results confirm that the proposed method, RReTX-ACK, improves the packet dissemination rate by approximately 8.30% within a 200 m distance from the source vehicle in an intersection scenario, compared to BReTX without using relay vehicles. © 2024 IEEE.

关键词： Magnetic levitation vehicles

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Hybrid Iterative Annealing Method Using a Quantum Annealer and a Classical computer

Hybrid Iterative Annealing Method Using a Quantum Annealer a...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Fukada, Keisuke Shirai, Tatshuhiko Togawa, Nozomu Waseda University Department of Computer Science and Communications Engineering Tokyo Japan

ISBN: (纸本)9798350324136

A combinatorial optimization problem is the problem of minimizing the energy function among many combinations of variables, which is often difficult to solve with conventional classical computers. Recently, Ising machines, including quantum annealers, have gained attention as a promising architecture for efficiently solving combinatorial optimization problems. Among various methods for solving such problems using Ising machines, one prominent approach is the three-stage annealing method. The approach effectively solves a combinatorial optimization problem, utilizing an initial solution, but it performs the annealing process only once. Repeating the annealing process several times may enhance the solution more efficiently. In this paper, we propose a novel hybrid iterative annealing method that consists of an initial process using a classical computer, an annealing process using a quantum annealer, and a correction process/selection process using a classical computer. The proposed method repeats the annealing process and the correction process/selection process until the solution is sufficiently converged. In the experimental evaluations through the two types of typical combinatorial optimization problems, the proposed method shows improvements by up to 50.5% compared to the three-stage annealing method. © 2024 IEEE.

关键词： combinatorial optimization problem hybrid iterative annealing Ising machine Quantum annealer

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Message Passing Detector for Phase-Shifter-Aided Spatial Multiplexing over Frequency Selective Channels

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8273-8278页

作者： Liu, Min Zhang, Lechen Chen, Jiangong Zammit, Saviour Xiao, Yue University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Malta Department of Communications and Computer Engineering MsidaMSD 2080 Malta

Reducing the cost of radio frequency (RF) chains remains a critical challenge in multiple-input multiple-output (MIMO) systems. In this paper, we investigate a novel low-RF-chain technique, termed as phase-shifter-aided spatial multiplexing (PSSM), in the context of frequency-selective channels. Base on the single-carrier frequency-domain equalization (SC-FDE) concept, we develop a message-passing detector specifically tailored for PSSM systems. This detector integrates belief propagation (BP) and expectation propagation (EP) to efficiently leverage prior constraints as well as handling the linear inverse problem. To further reduce computational complexity, a simplification method is then introduced. Simulation results demonstrate that the proposed framework achieves superior performance compared to conventional approaches. © 1967-2012 IEEE.

关键词： Inverse problems

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Entanglement-Controlled Quantum Federated Learning

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IEEE Internet of Things Journal 2025年第11期12卷 18318-18330页

作者： Park, Soohyun Lee, Hyunsoo Jung, Soyi Park, Jihong Bennis, Mehdi Kim, Joongheon The Division of Computer Science Sookmyung Women’s University Seoul04310 Korea Republic of The Department of Electrical and Computer Engineering Korea University Seoul02841 Korea Republic of The Department of Electrical and Computer Engineering Ajou University Suwon16499 Korea Republic of Singapore The Centre for Wireless Communications University of Oulu Oulu90014 Finland

According to the advances in quantum computing and distributed learning, quantum federated learning (QFL) has recently become an emerging field of study. In QFL, each quantum computer or device locally trains its quantum neural network (QNN) with trainable gates, and communicates only these gate parameters over classical channels, without costly quantum communications. To successfully opeate QFL under various and dynamic channel conditions in Internet of Things (IoT) environments, this paper develops a novel depth-controllable architecture of entangled slimmable quantum neural networks (eSQNNs), and thus, proposes an entangled slimmable QFL (eSQFL) that communicates the superposition-coded parameters of eSQNNs. Even though the proposed eSQNN-based eSQFL is superior, training the depth-controllable eSQNN architecture is challenging due to high entanglement entropy and inter-depth interference. Therefore, the proposed method in this paper mitigates the interference using entanglement controlled universal (CU) gates and an inplace fidelity distillation (IPFD) regularizer penalizing inter-depth quantum state differences, respectively. Furthermore, the proposed method optimizes the superposition coding power allocation by deriving and minimizing the convergence bound of eSQFL. The novelty of this work is evaluated via extensive simulations in terms of prediction accuracy, fidelity, and entropy compared to Vanilla QFL as well as under different channel conditions and various data distributions. © 2014 IEEE.

关键词： Federated learning

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Comparative review of the surround speaker virtualizers on DSP platform 32

Comparative review of the surround speaker virtualizers on D...

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32nd Telecommunications Forum, TELFOR 2024

作者： Sladek, Predrag Faculty of Technical Sciences University of Novi Sad Computer Engineering and Computer Communications Department Novi Sad Serbia

ISBN: (纸本)9798350391053

This paper reviews three DSP-based audio virtualizer implementations used in immersive audio technologies, which have transformed sound experiences with limited speaker setups. Focusing on key parameters such as memory usage, processing power, and input/output layouts, the study employs multi-criteria decision-making (MCDM) approach to evaluate each virtualizer's strengths and trade-offs. The findings provide insights into the efficiency and feasibility of these virtualizers in delivering high-quality immersive audio in resource-constrained environments. © 2024 IEEE.

关键词： Decision making

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Integrating DMA for Efficient 3D Audio Processing in Resource-Constrained DSP Systems 32

Integrating DMA for Efficient 3D Audio Processing in Resourc...

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32nd Telecommunications Forum, TELFOR 2024

作者： Cvetkovic, Katarina University of Novi Sad Faculty of Technical Sciences Computer Engineering and Computer Communications Department Novi Sad Serbia

ISBN: (纸本)9798350391053

In the rapidly advancing digital landscape, immersive sound technologies have emerged as transformative elements in enhancing user experiences across various media platforms, including film, gaming, and music. This paper explores the complexity of 3D audio, focusing on complex processing and volumes of data that meet contemporary broadcasting standards and enhances user interaction. We propose the integration of DMA to offer quick data access that enables advanced audio applications to operate within limited resources. © 2024 IEEE.

关键词： Static random access storage

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A Proactive Crowdsourcing Framework for Fake Base Station Detection and Avoidance 15

A Proactive Crowdsourcing Framework for Fake Base Station De...

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15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Saad, Omar A. Etman, Ahmed A. Abdel-Malek, Mai A. Azab, Mohamed Alexandria University Faculty of Engineering Department of Computer and Communications Engineering Alexandria Egypt The University of Arizona Department of Electrical and Computer Engineering AZ United States Virginia Military Institute Department of Computer and Information Sciences VA United States

ISBN: (纸本)9798331507695

With next-generation communication technologies becoming more integrated into critical infrastructure, securing these networks against sophisticated threats has become paramount. One of the most persistent threats to this communication is the growing presence of fake base stations (FBS). These FBSs are malicious entities that pose as legitimate base stations to intercept, manipulate, or exploit mobile communications, leading to serious privacy breaches. While some existing literature addresses the detection of such malicious entities, detecting FBSs has traditionally been the responsibility of network operators, who rely on tools like signal strength analysis and radio frequency (RF) monitoring to identify unusual patterns or rogue signals. However, these centralized methods often struggle to detect FBSs in complex environments characterized by high mobility, dense urban areas, and sophisticated spoofing techniques. This paper proposes a scalable and pervasive blockchain-based crowd-sourcing mechanism to enable extensive device participation in identifying FBSs. In a fully automated and distributed manner, the proposed platform uses vetted and verified information recorded on the blockchain to identify and report suspicious FBSs in the area. This allows other users to dissociate from these malicious entities automatically. A reputation management system is also employed to ensure the reliability and accountability of participating users. Using qualitative and quantitative evaluations, the proposed approach demonstrated effectiveness and efficiency in achieving all targeted goals. © 2025 IEEE.

关键词： Crowdsourcing

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Earthquake Analysis Using Long-Short Term Memory - LSTM

Earthquake Analysis Using Long-Short Term Memory - LSTM

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2024 International Conference on computer and Applications, ICCA 2024

作者： Salman, Ali El Mir, Gilbert Diab, Lea El Haber, Elias Haidar, Gaby Abou Achkar, Roger American University of Science and Technology Department of Computer & Communications Engineering Beirut Lebanon

ISBN: (纸本)9798350367560

The prediction and analysis of earthquakes have been a significant focus of scientific research for many years. Traditional methods have provided valuable insights, but their accuracy and dynamicity remain limited. The aim here is to address these challenges by employing deep learning techniques, specifically the Long Short-Term Memory (LSTM) algorithm, in conjunction with XGBoost as an ensemble learning technique. Earthquake analysis has been approached through various methodologies, with mixed results. Some methods have fallen short in delivering precise analysis, while others have grappled with the complexities of forecasting earthquakes. The introduction of deep learning in earthquake prediction has led to different outcomes compared to previous techniques. However, spatial distortion remains a persistent challenge. To tackle these challenges, this study utilizes the LSTM algorithm for global earthquake observation, combined with XGBoost. By employing influential and associated datasets, the model calculates a more accurate and straightforward time function. By combining the strengths of LSTM and XGBoost, this study aims to provide a more accurate and reliable earthquake analyzer model. The LSTM algorithm and XGBoost are addressing the challenges of spatial distortion and improving accuracy, dynamicity, and performance. © 2024 IEEE.

关键词： Long short-term memory

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