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arXiv 2022年

作者： Yang, Wanting Du, Hongyang Liew, Zi Qin Lim, Wei Yang Bryan Xiong, Zehui Niyato, Dusit Chi, Xuefen Shen, Xuemin Sherman Miao, Chunyan The Department of Communications Engineering Jilin University Changchun130012 China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore The School of Computer Science and Engineering The Energy Research Institute Ntu Interdisciplinary Nanyang Technological University Singapore Singapore Alibaba Group The Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Singapore School of Computer Science and Engineering Ntu Singapore Singapore The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada The School of Computer Science and Engineering Nanyang Technological University Singapore Singapore The Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Singapore The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University Singapore Singapore

With the increasing demand for intelligent services, the sixth-generation (6G) wireless networks will shift from a traditional architecture that focuses solely on a high transmission rate to a new architecture that is based on the intelligent connection of everything. Semantic communication (SemCom), a revolutionary architecture that integrates user as well as application requirements and the meaning of information into data processing and transmission, is predicted to become a new core paradigm in 6G. While SemCom is expected to progress beyond the classical Shannon paradigm, several obstacles need to be overcome on the way to a SemCom-enabled smart wireless Internet. In this paper, we first highlight the motivations and compelling reasons of SemCom in 6G. Then, we provide an overview of SemCom-related theory development. After that, we introduce three types of SemCom, i.e., semantic-oriented communication, goal-oriented communication, and semantic-aware communication. Following that, we organize the design of the communication system into three dimensions, i.e., semantic information (SI) extraction, SI transmission, and SI metrics. For each dimension, we review existing techniques and discuss their benefits and limitation, as well as the remaining challenges. Then, we introduce the potential applications of SemCom in 6G and portray the vision of future SemCom-empowered network architecture. Finally, we outline future research opportunities. In a nutshell, this paper provides a holistic review of the fundamentals of SemCom, its applications in 6G networks, and the existing challenges and open issues with insights for further in-depth investigations. Copyright © 2022, The Authors. All rights reserved.

关键词： Network architecture

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An Evolutionary Pathway for the Quantum Internet Relying on Secure Classical Repeaters

arXiv

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arXiv 2022年

作者： Long, Gui-Lu Pan, Dong Sheng, Yu-Bo Xue, Qikun Lu, Jianhua Hanzo, Lajos State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University The Frontier Science Center for Quantum Information Beijng 100084 China Beijing Academy of Quantum Information Sciences Beijing100193 China College of Electronic and Optical Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Southern University of Science and Technology Shenzhen518055 China School of Information Science and Technology Tsinghua University The Beijing National Research Center for Information Science and Technology The Frontier Science Center for Quantum Information Beijing100084 China School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Until quantum repeaters become mature, quantum networks remain restricted either to limited areas of directly connected nodes or to nodes connected to a common node. We circumvent this limitation by conceiving quantum networks using secure classical repeaters combined with the quantum secure direct communication (QSDC) principle, which is a compelling form of quantum communication that directly transmits information over quantum channel. The final component of this promising solution is our classical quantum-resistant algorithm. Explicitly, in these networks, the ciphertext gleaned from a quantum-resistant algorithm is transmitted using QSDC along the nodes, where it is read out and then transmitted to the next node. At the repeaters, the information is protected by our quantum-resistant algorithm, which is secure even in the face of a quantum computer. Hence, our solution offers secure end-to-end communication across the entire network, since it is capable of both eavesdropping detection and prevention in the emerging quantum internet. It is compatible with operational networks, and will enjoy the compelling services of the popular Internet, including authentication. Hence, it smoothens the transition from the classical Internet to the Quantum Internet (Qinternet) by following a gradual evolutionary upgrade. It will act as an alternative network in quantum computing networks in the future. We have presented the first experimental demonstration of a secure classical repeater based hybrid quantum network constructed by a serial concatenation of an optical fiber and free-space communication link. In conclusion, secure repeater networks may indeed be constructed using existing technology and continue to support a seamless evolutionary pathway to the future Qinternet of quantum computers. © 2022, CC BY.

关键词： Quantum computers

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Toward Beamfocusing-Aided Near-Field Communications: Research Advances, Potential, and Challenges

arXiv

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arXiv 2023年

作者： An, Jiancheng Yuen, Chau Dai, Linglong Di Renzo, Marco Debbah, Mérouane Hanzo, Lajos The School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore The Beijing National Research Center for Information Science and Technology The Department of Electronic Engineering Tsinghua University Beijing100084 China Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes Gif-sur-Yvette91192 France Khalifa University of Science and Technology P O Box 127788 Abu Dhabi United Arab Emirates The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Next-generation mobile networks promise to support high throughput, massive connectivity, and improved energy efficiency. To achieve these ambitious goals, extremely large-scale antenna arrays (ELAAs) and terahertz communications constitute a pair of promising technologies. This will result in future wireless communications occurring in the near-field regions. To accurately portray the channel characteristics of near-field wireless propagation, spherical wavefront-based models are required and present both opportunities as well as challenges. Following the basics of near-field communications (NFC), we contrast it to conventional far-field communications. Moreover, we cover the key challenges of NFC, including its channel modeling and estimation, near-field beamfocusing, as well as hardware design. Our numerical results demonstrate the potential of NFC in improving the spatial multiplexing gain and positioning accuracy. Finally, a suite of open issues are identified for motivating future research. Copyright © 2023, The Authors. All rights reserved.

关键词： Antenna arrays

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String-Breaking Dynamics in Quantum Adiabatic and Diabatic Processes

arXiv

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arXiv 2024年

作者： Surace, Federica Maria Lerose, Alessio Katz, Or Bennewitz, Elizabeth R. Schuckert, Alexander Luo, De De, Arinjoy Ware, Brayden Morong, William Collins, Kate Monroe, Christopher Davoudi, Zohreh Gorshkov, Alexey V. Department of Physics Institute for Quantum Information and Matter California Institute of Technology PasadenaCA91125 United States Rudolf Peierls Centre for Theoretical Physics Clarendon Laboratory OxfordOX1 3PU United Kingdom Institute for Theoretical Physics KU Leuven Celestijnenlaan 200D Leuven3001 Belgium Duke Quantum Center Departments of Physics and Electrical and Computer Engineering Duke University DurhamNC27708 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Department of Physics Maryland Center for Fundamental Physics University of Maryland College ParkMD20742 United States

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking: the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

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A deep learning based wearable healthcare iot device for ai-enabled hearing assistance automation 19

A deep learning based wearable healthcare iot device for ai-...

引用

19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Young, Fraser Zhang, Li Jiang, Richard Liu, Han Wall, Conor Northumbria University Department of Computer and Information Sciences NewcastleNE1 8ST United Kingdom Lancaster University School of Computing and Communications Faculty of Science and Technology Lancaster United Kingdom Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

ISBN: (纸本)9780738124261

With the recent booming of artificial intelligence (AI), particularly deep learning techniques, digital healthcare is one of the prevalent areas that could gain benefits from AI-enabled functionality. This research presents a novel AI-enabled Internet of Things (IoT) device operating from the ESP-8266 platform capable of assisting those who suffer from impairment of hearing or deafness to communicate with others in conversations. In the proposed solution, a server application is created that leverages Google's online speech recognition service to convert the received conversations into texts, then deployed to a micro-display attached to the glasses to display the conversation contents to deaf people, to enable and assist conversation as normal with the general population. Furthermore, in order to raise alert of traffic or dangerous scenarios, an 'urban-emergency' classifier is developed using a deep learning model, Inception-v4, with transfer learning to detect/recognize alerting/alarming sounds, such as a horn sound or a fire alarm, with texts generated to alert the prospective user. The training of Inception-v4 was carried out on a consumer desktop PC and then implemented into the AI-based IoT application. The empirical results indicate that the developed prototype system achieves an accuracy rate of 92% for sound recognition and classification with real-time performance. © 2020 IEEE.

关键词： Internet of things

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Volatile to Non-Volatile Switching Transition in Chalcogenides

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Advanced Functional Materials 2025年第23期35卷

作者： Zhao, Zihao Zhang, Mengfei Yang, Qun Gotoh, Tamihiro Ge, Qingqin Shi, Nannan Sun, Yuting Zhao, Jiayi Sui, Yanping Jiang, Ran Yu, Haibin Elliott, Stephen R. Song, Zhitang Zhu, Min National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Micro-System and Information Technology Chinese Academy of Sciences Shanghai200050 China University of Chinese Academy of Sciences Beijing100029 China Wuhan National High Magnetic Field Center and School of Physics Huazhong University of Science and Technology Wuhan430074 China Department of Physics Graduate School of Science and Technology Gunma University Maebashi3718510 Japan Thermo Fisher Scientific China Shanghai200050 China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Trinity College University of Cambridge CambridgeCB2 1TQ United Kingdom Physical and Theoretical Chemistry Laboratory University of Oxford OxfordOX1 3QZ United Kingdom School of Integrated Circuits Shanghai Jiao Tong University Shanghai200240 China

Over the past 60 years, three distinct electrical switching behaviors have been discovered in chalcogenides: ovonic threshold switch (OTS), ovonic memory switch (OMS), and phase-change switch (PCS). The first two have been successfully utilized in commercialized 3D Xpoint chips, serving as selector and memory cells, respectively. However, the relationships among these three behaviors remain unclear. Here, it is demonstrated that the Ge-Te binary system exhibits these three switching mechanisms. Specifically, the switching behavior transforms from PCS-like to OTS-like within the composition range from GeTe8 to GeTe6, while the shift from volatile (OTS) to non-volatile switching behavior (OMS) occurs between the compositions GeTe2 and GeTe. The PCS-to-OTS transition is primarily driven by enhancements in glass-forming ability, with the Turnbull parameter increasing from 0.58 to 0.6, and the crystallization temperature exceeding 145 °C, while the shift from OTS to OMS behavior is largely due to the significantly accelerated crystallization speed, from microseconds to nanoseconds. Most importantly, the GeTe16 PCS stands out, with a large ON current (0.6 mA), low leakage current (−8 A), high endurance (>6 × 109 cycles), and high-temperature back-end-of-line compatibility. The crystalline nature of this PCS material addresses the composition and toxicity issues in conventional OTS materials. Moreover, GeTe16 PCSs have been successfully integrated with GeTe OMSs, forming selector/memory arrays with a read margin of 0.4 V. These findings not only reveal the mechanisms underlying the volatile to non-volatile transition but also provide an alternative solution for high-density 3D memory, potentially replacing the OTS/OMS stack approach. © 2025 Wiley-VCH GmbH.

关键词： Phase change memory

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Designed Features for Improving Openness, Scalability and Programmability in the Fog Computing-Based IoT Systems

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SN computer Science 2020年第4期1卷 1-12页

作者： Tran, Quang Minh Nguyen, Phat Huu Tsuchiya, Takeshi Toulouse, Michel Department of Information Systems Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology 268 Ly Thuong Kiet District 10 Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh City Viet Nam School of Electronics and Telecommunications Hanoi University of Science and Technology No. 1 Dai Co Viet Road Hanoi Viet Nam Department of Applied Information Engineering Faculty of Engineering Suwa University of Science Nagano Japan School of Information and Communication Technology Hanoi University of Science Technology No. 1 Dai Co Viet Road Hanoi Viet Nam

Global-scale Internet of Things (IoT) applications commonly process a huge amount of data and quickly provide useful information (to users) and instructions to monitor or control the physical world;most of these services are required to be of low latency while satisfying resource constraints (computing, storage, networking). In order to reduce communication latency, network load, energy consumption and operational cost which are essential for real-world IoT applications, fog computing is a promising technology as it allows utilizing virtualized resources already available on the network edges which are close to IoT data generators (IoT devices) and consumers (users or actuators). However, there are still many challenges in realizing this computing paradigm as it is still in the infancy stage. This paper investigates and proposes designed features for the “openness,” “scalability” and “programmability” in fog computing to which IoT services/applications can be flexibly implemented in the fog landscape. We apply the proposed mechanism to a real-world application, namely the traffic light optimization problem, to validate its effectiveness and feasibility. The evaluation results reveal the effectiveness of the proposed approach. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Edge/Fog computing Flexibility IoTs Openness Programmability

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Digital Health and Deep Learning: Opportunities, Challenges, and the Imperative of Data Protection in Wearable Devices

SSRN

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SSRN 2024年

作者： Norman, Azah Anir Eke, Christopher Ifeanyi Phiri, Musa Al-Garadi, M.A. Ahmed, Abdulaziz Yeh, Wan-Ju Department of Information System FCSIT University of Malaya Malaysia Department of Computer Science Faculty of Computing Federal University of Lafia Nasarawa state Nigeria Department of Engineering and Technology Mulungushi University PO Box 80415 Kabwe Zambia Department of Biomedical Informatics School of Medicine Vanderbilt University 1161 21st Ave S # D3300 NashvilleTN37232 United States Department of Health Services Administration School of Health Professions University of Alabama at Birmingham 1716 9th Ave S BirminghamAL35233 United States National Cheng-Kung University Department of Law No. 1 University Road Tainan City70 Taiwan

The rapid expansion of digital health technologies has been revolutionized by the combination of deep learning and machine learning models with wearable devices, making it possible to perform sophisticated data analytics, predictive health analytics, and real-time monitoring. The paper examines the fascinating possibilities of deep learning, wearable technology, and digital health while emphasizing the challenges and urgent need for data protection. Deep learning and digital health hold great promise for individualized treatment plans, early disease identification, and ongoing health monitoring. Large volumes of health data can be analyzed by machine learning/deep learning models, which can then produce findings and recommendations that are timely and instructive for patients, doctors, and scholars. However, these opportunities also provide significant challenges such as security and privacy. It becomes critical to protect data against misuse, unauthorized access, and data breaches. Strong data protection protocols, compliance with legal requirements, and ethical considerations to uphold user trust are necessary for ensuring the responsible use of machine learning/algorithms in the healthcare industry. This article also highlights the significance of encouraging transparency, guaranteeing accountability among business players, and developing data protection rules and guidelines for wearable devices. Collaboration between policymakers, healthcare professionals, researchers, and technology developers are essential to address the ethical, legal, and technical complexities surrounding data protection in wearable healthcare devices. By addressing the challenges and imperative of data protection, stakeholders can shape a responsible and secure landscape for digital health and deep learning applications, ensuring the long-term success and adoption of wearable devices in healthcare. © 2024, The Authors. All rights reserved.

关键词： Wearable technology

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Behaviour-constrained support vector machines for FMRI data analysis

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AIP Conference Proceedings 2023年第1期2523卷

作者： Pardeep Kumar J. Jegan Amarnath K. Somasundaram Thilagavathy A. 1Department of Artificial Intelligence Anurag University Hyderabad Telangana India. 2Department of Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India. 3Department of Computer Science and Engineering Chennai Institute of Technology Malayambakkam Chennai Tamil Nadu India. 4Department of Computer Science and Engineering R.M.K. Engineering College Chennai Tamil Nadu India.

Statistical learning approaches, including SVM, are a powerful tool for studying functional imaging data. These were especially effective in extracting information from useful magnetic resonance imaging signals from the direction and location of visual properties and categories of objects. Computational intelligence methods are developed to decipher neural imagery information as a valuable tool. The distorted signal and the small number of test patterns usually reported in functional brain imaging studies pose problems when interpreting brain data by using predictive learning techniques. To solve this issue, we propose to use previous details focused on human observers’ behavioral success to boost the training of Support Vector Machines (SVMs). During functional resonance screening, we gather behavioral reactions to human participants executing a classified mission. We use the brain imaging method developed based on the behavioral choices of observers as a distance limit for SVM training. We name the behaviourally limited SVM process. Our results show that BCSVM consistently outperforms SVM.

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Modeling for small cell networks in 5G communication environment

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Telecommunication Systems 2022年第2期80卷 189-214页

作者： Kim, Tae-Yeun Singh, A. K. Ko, Hoon National Program of Excellence in Software Center Chosun University Gwangju Republic of Korea Department of Computer Science and Engineering National Institute of Technology Patna Patna India Research Institute of Computer Information Communications Chungbuk National University E8-7 Chungdae-ro 1 Seowon-ku Chungcheongbuk-do South Korea Instituto Superior de Engenharia do Porto Instituto Politecnico do Porto R. Dr. Antonio Bernardino de Almeida 431 Porto Portugal

The small cell structure in which many cells are arranged per unit area by reducing the size of cells is a candidate technology for an increase in transmission capacity in the 5G environment. However, the decrease in the size of the cell led to additional problems such as increased inter cell interference and frequent cell changes owing to the movement of the terminal. Therefore, the aim of this study was to propose small cell dynamic channel allocation (SDCA) and hybrid and dynamic channel allocation (HDCA) using conventional reuse methods to improve the macro cell performance while efficiently utilizing scarce frequency resources. The proposed method facilitates an improved performance that is lacking for macro-cell users in the center area of the cell boundary for the network where conventional macro cells and small cells are superposed. Furthermore, to improve the performance, it can provide resources that are lacking in the small cells of the center. To evaluate the performance, the proposed method was compared to frequency reuse factor1 (FRF1), frequency reuse factor3 (FRF3), and fractional frequency reuse (FFR) methods in terms of the signal-to-interference/noise-ratio (SINR) of users of each macro cell and small cell, outage, capacity for each user, and total system capacity. As a result of comparing the SINR, it was confirmed that the performance of the macro cell users has improved by an average of 43.88% compared to FRF1, FRF3, and FFR, and the performance of small cell users has improved by an average of 4.31%. Comparison results show that the outage proportions of the macro and small cell users are 61.29% and 70.59% lower on average, respectively. A comparison of results show that the capacities of the macro and small cell users have also improved by 22.5% and 14.5% on average, respectively. As the comparison results of the total system capacity indicate, the proposed method shows an average improvement of 11.67%. In cases in which the added resources o

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