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Joint Trajectory and Beamforming Optimization for UAV-Relayed Integrated Sensing and Communication with Mobile Edge Computing

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IEEE Transactions on Mobile Computing 2025年

作者： Xu, Shanfeng Liu, Zhipeng Zhao, Le Liu, Ziyi Wang, Xinyi Fei, Zesong Nallanathan, Arumugam Beijing Institute of Technology School of Information and Electronics Beijing100081 China China Academy of Electronics and Information Technology Beijing100041 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

In this paper, we investigate joint trajectory and beamforming design for unmanned aerial vehicle (UAV)-relayed integrated sensing and communication (ISAC) systems with mobile edge eomputing (MEC) under the clutter environment. Due to the limited on-board computing capability, the UAV has to offload sensing echoes to the base station (BS) for efficient processing. A novel relay-based ISAC-then-offload frame structure is considered. We aim to maximize the throughput of the BS-UAV-user relaying link while ensuring sensing accuracy and efficient sensing data offloading. The non-convex problem is solved using an alternating optimization algorithm based on successive convex approximation (SCA). Simulation results illustrate that our proposed algorithm achieves near-optimal communication performance while guaranteeing sensing accuracy, addressing the balance between the communication and sensing performance. Furthermore, we evaluate the impact of critical system parameters including sensing constraints, power control factor, and UAV flight duration on communication performance, and explore the trade-offs between energy efficiency and spectral efficiency under varying sensing data intensity and offloading duration. © 2025 IEEE.

关键词： Drones

Resource-efficient fault-tolerant one-way quantum repeater with code concatenation

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arXiv 2023年

作者： Wo, Kah Jen Avis, Guus Rozpędek, Filip Mor-Ruiz, Maria Flors Pieplow, Gregor Schröder, Tim Jiang, Liang Sørensen, Anders S. Borregaard, Johannes QuTech Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Quantum Technologies National University of Singapore Queenstown117543 Singapore Quantum Computer Science EEMCS Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Kavli Institute of Nanoscience Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States College of Information and Computer Sciences University of Massachusetts Amherst AmherstMA01003 United States Universität Innsbruck Institut für Theoretische Physik Technikerstraße 21a Innsbruck6020 Austria Department of Physics Humboldt-Universität zu Berlin Newtonstraße 15 Berlin12489 Germany The Niels Bohr Institute University of Copenhagen Blegdamsvej 17 Copenhagen ØDK-2100 Denmark

One-way quantum repeaters where loss and operational errors are counteracted by quantum error correcting codes can ensure fast and reliable qubit transmission in quantum networks. It is crucial that the resource requirements of such repeaters, for example, the number of qubits per repeater node and the complexity of the quantum error correcting operations are kept to a minimum to allow for near-future implementations. To this end, we propose a one-way quantum repeater that targets both the loss and operational error rates in a communication channel in a resource-efficient manner using code concatenation. Specifically, we consider a tree-cluster code as an inner loss-tolerant code concatenated with an outer 5-qubit code for protection against Pauli errors. Adopting flag-based stabilizer measurements, we show that intercontinental distances of up to 10,000 km can be bridged with a minimized resource overhead by interspersing repeater nodes that each specializes in suppressing either loss or operational errors. Our work demonstrates how tailored error-correcting codes can significantly lower the experimental requirements for long-distance quantum communication. © 2023, CC BY.

关键词： Concatenated codes

The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII (vol 2024, baae069, 2024)

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DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2024年第2024期2024卷 baae069页

作者： Islamaj, Rezarta Lai, Po-Ting Wei, Chih-Hsuan Luo, Ling National Center for Biotechnology Information (NCBI) National Library of Medicine (NLM) National Institutes of Health (NIH) 8600 Rockville Pike Bethesda MD 20894 United States School of Computer Science and Technology Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian 116024 China Department of Electronics Telecommunications and Informatics (DETI) Institute of Electronics and Informatics Engineering of Aveiro (IEETA) University of Aveiro Campus Universitário de Santiago Aveiro 3810-193 Portugal Departamento de Informática Faculdade de Ciências da Universidade de Lisboa Edifício C6 Campo Grande Lisbon 1749-016 Portugal Department of Computer Science and Information Engineering National Cheng Kung University No.1 University Road Tainan City 701 Taiwan Republic of China Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd. Zhongli District Taoyuan City 32001 Taiwan Republic of China Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd. Nangang District Taoyuan City 115201 Taiwan Republic of China School of Information Sciences University of Illinois at Urbana-Champaign 614 E. Daniel St Champaign IL 61820 United States Higher School of Economics University 20 Myasnitskaya st Moscow 101000 Russia Kazan Federal University 18 Kremlevskaya st Kazan Russia 420008 Russia Miin Wu School of Computing National Cheng Kung University No. 1 University Road Tainan 701 Taiwan Republic of China School of Computing Technologies RMIT University 124 La Trobe Street Melbourne Victoria 3000 Australia

The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many biomedical natural language processing (NLP) applications, from drug discovery to custom medical solutions. The BioRED track simulates a real-world application of biomedical relationship extraction, and as such, considers multiple biomedical entity types, normalized to their specific corresponding database identifiers, as well as defines relationships between them in the documents. The challenge consisted of two subtasks: (i) in Subtask 1, participants were given the article text and human expert annotated entities, and were asked to extract the relation pairs, identify their semantic type and the novelty factor, and (ii) in Subtask 2, participants were given only the article text, and were asked to build an end-to-end system that could identify and categorize the relationships and their novelty. We received a total of 94 submissions from 14 teams worldwide. The highest F-score performances achieved for the Subtask 1 were: 77.17% for relation pair identification, 58.95% for relation type identification, 59.22% for novelty identification, and 44.55% when evaluating all of the above aspects of the comprehensive relation extraction. The highest F-score performances achieved for the Subtask 2 were: 55.84% for relation pair, 43.03% for relation type, 42.74% for novelty, and 32.75% for comprehensive relation extraction. The entire BioRED track dataset and other challenge materials are available athttps://***/pub/lu/BC8-BioRED-track/andhttps://***/competitions/13377andhttps://***/competitions/*** URL:https://***/pub/lu/BC8-BioRED-track/https://***/competitions/13377https://***/competitions/13378

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Lyapunov stability of the numerical solution of the Saint-Venant equation

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AIP Conference Proceedings 2023年第1期2484卷

作者： R. Aloev I. Abdullah A. Akbarova S. H. Juraev 1Department of Computational Mathematics and Information Systems National University of Uzbekistan Uzbekistan Almazar 4 Tashkent Uzbekistan. 2Faculty of Ocean Engineering Technology and Informatics University Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia.

The work is devoted to the study of the stability of the finite difference method for the initial-boundary value problem for the system of Saint-Venant equations. Easily the verifiable practical stability conditions have been obtained. Energy estimates are established for an approximate solution of a discrete initial-boundary value problem. This energy estimate allows us to assert the stability of the finite difference method. The corresponding stability theorem is proved. The discrete Lyapunov function is constructed. An a priori estimate is obtained for the numerical solution of the boundary-value difference problem. This estimate allows us to speak about the exponential stability of the numerical solution.

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Sensing-Communication-Computing-Control Closed-Loop Optimization for 6G Digital Twin-Empowered Unmanned Robotic Systems

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IEEE Journal on Selected Areas in Communications 2025年

作者： Fang, Xinran Lei, Chengleyang Feng, Wei Chen, Yunfei Xiao, Ming Ge, Ning Wang, Cheng-Xiang Tsinghua University State Key Laboratory of Space Network and Communications Department of Electronic Engineering Beijing100084 China University of Durham Department of Engineering DurhamDH1 3LE United Kingdom Royal Institute of Technology School of Electrical Engineering and Computer Science Department of Information Science and Engineering Sweden Southeast University National Mobile Communications Research Laboratory School of Information Science and Engineering Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

In recent decades, cyber-physical systems (CPSs) have received great attention due to their broad applications. This paper investigates CPS deployment in remote areas, specifically focusing on a digital twin-empowered unmanned robotic system. The system consists of a multifunctional unmanned aerial vehicle (UAV), sensors, and actuators. The UAV carries communication and computing modules, acting as an edge information hub (EIH) that connects sensors and actuators - forming reflex-arc-like sensing-communication-computing-control (SC3) loops. A digital twin is integrated into the EIH to emulate the system's behavior and assist in the decision-making. To alleviate resource limitations in remote areas, we propose a goal-oriented closed-loop optimization scheme. The proposed scheme takes the SC3 loop as an integrated structure and jointly optimizes uplink and downlink (UL&DL) communication and computing resources to minimize the total linear quadratic regulator (LQR) cost. To address the non-convex optimization problem, we derive the closed-form solution for intra-loop allocation and propose an efficient iterative algorithm for inter-loop optimization. Under the condition of adequate CPU frequency, we derive an approximate closed-form solution for inter-loop bandwidth allocation. Simulation results demonstrate the superiority of the proposed scheme, which achieves a two-tier task-level balance within and across the SC3 loops. © 1983-2012 IEEE.

关键词： Drones

Completion time minimization in wireless-powered UAV-assisted data collection system (Full Version)

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arXiv 2021年

作者： Wang, Zhen Zhang, Guopeng Wang, Qiu Wang, Kezhi Yang, Kun The Engineering Research Center of Mine Digitalization of Ministry of Education China University of Mining and Technology Xuzhou221116 China The School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China The Department of Computer and Information Science Northumbria University NewcastleNE2 1XE United Kingdom The School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park ColchesterCO4 3SQ United Kingdom

In unmanned aerial vehicle (UAV)-assisted data collection system, UAVs can be deployed to charge ground terminals (GTs) via wireless power transfer (WPT) and collect data from them via wireless information transmission (WIT). In this paper, we aim to minimize the time required by a UAV via jointly optimizing the trajectory of the UAV and the transmission scheduling for all the GTs. This problem is formulated as a mixed integer nonlinear programming (MINLP) which are difficult to address in general. To this end, we develop an iterative algorithm based on binary search and successive convex optimization (SCO) to solve it. The simulation shows that our proposed solution outperforms the benchmark algorithms. © 2021, CC BY.

关键词： Unmanned aerial vehicles (UAV)

Practical Authentication Scheme Preserving Privacy Protection for the Internet of Things 3rd

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Practical Authentication Scheme Preserving Privacy Protectio...

3rd International Conference on Security with Intelligent Computing and Big-data Services, SICBS 2019

作者： Tsai, Kuo-Yu Lai, Ching-Wei Fu, Chen-Hua Wang, Chi-Hung Hwang, Yuh-Shyan Department of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Road Seatwen Taichung407 Taiwan Department of Information Management National Defense University No. 70 Sec. 2 Zhongyang N. Road Beitou District Taipei112 Taiwan Department of Electronic Engineering National Taipei University of Technology No. 1 Sec. 3 Zhongxiao E. Road Taipei106 Taiwan

ISBN: (纸本)9783030468279

Based on the authentication scheme of Wu et al. (published in the Journal of Ambient Intelligence and Humanized Computing, Volume 8, Issue 1, pp 101–116, 2017), we propose a robust privacy protection authentication scheme to prevent malicious attacks in general wireless sensor networks. In addition, we implement the proposed scheme in Rasperry Pi to simulate a home monitoring system and validate the feasibility of the proposed method. © Springer Nature Switzerland AG 2020.

关键词： Internet of things

Deep Reinforcement Learning-Based Long-Range Autonomous Valet Parking for Smart Cities

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arXiv 2021年

作者： Khalid, Muhammad Wang, Liang Wang, Kezhi Pan, Cunhua Aslam, Nauman Cao, Yue The Department of Computer Science and Technology University of Hull HullHU6 7RX United Kingdom The Department of Computer and Information Science Northumbria University Newcastle upon TyneNE1 8ST United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London E1 4NS United Kingdom School of Cyber Science and Engineering Wuhan University Wuhan430072 China

In this paper, to reduce the congestion rate at the city center and increase the travelling quality of experience (QoE) of each user, the framework of long-range autonomous valet parking (LAVP) is presented, where an Autonomous Vehicle (AV) is deployed can pick up, drop off users at their required spots, and then drive to the car park around well organized places of city autonomously. In this framework, we aim to minimize the overall distance of the AV, while guarantee all users are served with great QoE, i.e., picking up, and dropping off users at their required spots through optimizing the path planning of the AV and number of serving time slots. To this end, we first propose a learning based algorithm, which is named as Double-Layer Ant Colony Optimization (DL-ACO) algorithm to solve the above problem in an iterative way. Then, to make the real-time decision, while considers the dynamic environment (i.e., the AV may pick up and drop off users from different locations), we further present a deep reinforcement learning (DRL) based algorithm, which is known as deep Q-learning network (DQN). The experimental results show that the DL-ACO and DQN-based algorithms both achieve the considerable performance. © 2021, CC BY.

关键词： Ant colony optimization

Deep Learning Driven Buffer-Aided Cooperative Networks for B5G/6G: Challenges, Solutions, and Future Opportunities

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arXiv 2024年

作者： Xu, Peng Chen, Gaojie Quan, Jianping Huang, Chong Krikidis, Ioannis Wong, Kai-Kit Chae, Chan-Byoung The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The Chongqing Key Laboratory of Mobile Communications Technology Chongqing400065 China State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangdong China Home for 5GIC & 6GIC University of Surrey Guildford SurreyGU2 7XH United Kingdom The Dept. of Electrical and Computer Engineering University of Cyprus Kallipoleos 75 Nicosia1678 Cyprus The Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Yonsei Frontier Lab. Yonsei University Seoul03722 Korea Republic of The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of

Buffer-aided cooperative networks (BACNs) have garnered significant attention due to their potential applications in beyond fifth generation (B5G) or sixth generation (6G) critical scenarios. This article explores various typical application scenarios of buffer-aided relaying in B5G/6G networks to emphasize the importance of incorporating BACN. Additionally, we delve into the crucial technical challenges in BACN, including stringent delay constraints, high reliability, imperfect channel state information (CSI), transmission security, and integrated network architecture. To address the challenges, we propose leveraging deep learning-based methods for the design and operation of B5G/6G networks with BACN, deviating from conventional buffer-aided relay selection approaches. In particular, we present two case studies to demonstrate the efficacy of centralized deep reinforcement learning (DRL) and decentralized DRL in buffer-aided non-terrestrial networks. Finally, we outline future research directions in B5G/6G that pertain to the utilization of BACN. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning