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arXiv 2024年

作者： Sagar, Srinivas Subhash, Athira Liu, Chen-Feng Elzanaty, Ahmed Al-Badarneh, Yazan H. Kalyani, Sheetal Alouini, Mohamed-Slim Bennis, Mehdi Hanzo, Lajos Dept. of Electrical Engg. IIT Madras India Department of Informatics New Jersey Institute of Technology NewarkNJ07102 United States University of Surrey GuildfordGU2 7XH United Kingdom Department of Electrical Engineering The University of Jordan Amman11942 Jordan Makkah Province Thuwal Saudi Arabia Centre for Wireless Communications University of Oulu Oulu90014 Finland School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Promising technologies such as massive multiple-input and multiple-output, reconfigurable intelligent reflecting surfaces, non-terrestrial networks, millimetre wave communication, ultra-reliable low-latency communication are envisioned as the enablers for next-generation (NG) networks. In contrast to conventional communication systems meeting specific average performance requirements, NG systems are expected to meet quality-of-service requirements in extreme scenarios as well. In this regard, extreme value theory (EVT) provides a powerful framework for the design of communication systems. In this paper, we provide a comprehensive survey of advances in communication that utilize EVT to characterize the extreme order statistics of interest. We first give an overview of the history of EVT and then elaborate on the fundamental theorems. Subsequently, we discuss different problems of interest in NG communication systems and how EVT can be utilized for their analysis. We finally point out the open challenges and future directions of EVT in NG communication systems. Copyright © 2024, The Authors. All rights reserved.

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

arXiv

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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

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Spectral efficiency optimization for hybrid relay-reflecting intelligent surface

arXiv

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arXiv 2021年

作者： Nguyen, Nhan Thanh Vu, Quang-Doanh Lee, Kyungchun Juntti, Markku Centre for Wireless Communications University of Oulu P.O.Box 4500 FI-90014 Finland The Mobile Networks Nokia Oulu90650 Finland Dept. of Electrical and Information Engineering Seoul National University of Science and Technology Seoul Korea Republic of

We propose a novel concept of hybrid relay-reflecting intelligent surface (HR-RIS), in which a single or few elements are deployed with power amplifiers (PAs) to serve as active relays, while the remaining elements only reflect the incident signals. The design and optimization of the HR-RIS is formulated in a spectral efficiency (SE) maximization problem, which is efficiently solved by the alternating optimization (AO) method. The simulation results show that a significant improvement in the SE can be attained by the proposed HR-RIS, even with a limited power budget, with respect to the conventional reconfigurable intelligent surface (RIS). In particular, the favorable design and deployment of the HR-RIS are analytically derived and numerically justified. © 2021, CC BY.

关键词： Power amplifiers

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Introduction of the Study Results of the Moon Electrical Power Systems 22

Introduction of the Study Results of the Moon Electrical Pow...

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22nd IAA Symposium on Building Blocks for Future Space Exploration and Development at the 75th International Astronautical Congress, IAC 2024

作者： Oka, Noriaki Yamauchi, Kenji Ijichi, Koichi Yanagawa, Hiroki Kashimura, Osamu Uchida, Atsushi Tanaka, Koji Mitani, Tomohiko Honjo, Kazuhiko Ishikawa, Ryo Ishimura, Kosei Fujino, Yoshiyuki Fujita, Kazuhisa Itoh, Kenji Kawakami, Yoshihiro Ishikawa, Yoji Yamaguchi, Hiroshi Ogawa, Akihiko Japan Space Systems 3-5-8 Shibakoen Minato-ku Tokyo105-0011 Japan Emerging Technologies and Security Division Mitsubishi Research Institute Inc. 10-3 Nagatacho 2-chome Chiyoda-ku Tokyo100-8141 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo-ku Kanagawa Sagamihara252-5210 Japan Kyoto University Gokasho Kyoto Uji611-0011 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Dept. of Modern Mechanical Engineering School of Creative Science and Engineering Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo169-8555 Japan Faculty of Science and Engineering Toyo University 2100 Kujirai Saitama-ken Kawagoe350-8585 Japan 1955-1 Kurematsu-cho chuo-ku Shizuoka Hamamatsu431-1202 Japan Department of Electrical and Electronic Engineering College of Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Ishikawa Nonoichi921-8501 Japan Obayashi Future Lab. Technology Division Obayashi Corporation 2-15-2 Konan Minato-ku Tokyo108-8502 Japan 492 Minosho-machi Nara-ken YamatoKoriyama639-1186 Japan Electronics Technologies Office Technologies Development Department IHI Aerospace Co. Ltd. 900 Fujiki Gunma-ken Tomioka-shi370-2398 Japan

ISBN: (纸本)9798331312251

Since the year of 2021, Ministry of Economy, Trade and Industry (METI) started work on the energy issues on the Moon including the feasibility study of the electrical power system with Mitsubishi Research Institute, Japan Space Systems, Institute of Space and Astronautical Science of Japan Aerospace Exploration Agency (JAXA), the universities and the industries. The architecture of the Moon electrical power infrastructure is found to be more like those of the power infrastructure of the earth than current satellite power system, and consisted of the power generation, power distribution grid and the power storage, and supplying electrical power to the consumer. The differences are that the environment of the Moon such as the vacuum and temperature condition, the influence of the regolith, etc. should have to be considered, and also the transportation cost of the construction is the key factor for the necessary technology to be selected. Of course, the technologies already established by the International Space Station (ISS) should be applied where necessary such as in the human habitable area. And more feature of the Moon is that the power generation on the Moon orbit and be sent to the surface or the inside the Permanent Shadow Region (PSR) other than on the surface of the Moon. The main consumer of the power system until the year 2050th is the water extraction and then the electrolysis of the water for, such as, the propellant for the transportation means and the electricity for the human habitant. The results of the system feasibility study of the Moon power architecture and also the electric power system team activities including the discussion with the hydrogen production team are going to be introduced. Copyright © 2024 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Space power generation

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Computational Approaches to Explainable Artificial Intelligence: Advances Intheory, Applications and Trends

SSRN

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SSRN 2023年

作者： Górriz, Juan Manuel Álvarez-Illán, I. Álvarez-Marquina, A. Arco, J.E. Atzmueller, M. Ballarini, F. Barakova, E. Bologna, G. Bonomini, P. Castellanos-Dominguez, G. Castillo-Barnes, D. Cho, S.B. Contreras, R. Cuadra, J.M. Domínguez, E. Domínguez-Mateos, F. Duro, R.J. Elizondo, D. Fernández-Caballero, A. Fernandez-Jover, E. Formoso, M.A. Gallego-Molina, N.J. Gamazo, J. García González, J. Garcia-Rodriguez, J. Garre, C. Garrigós, J. Gómez-Rodellar, A. Gómez-Vilda, P. Graña, M. Guerrero-Rodriguez, B. Hendrikse, S.C.F. Jimenez-Mesa, C. Jodra-Chuan, M. Julian, V. Kotz, G. Kutt, K. Leming, M. de Lope, J. Macas, B. Marrero-Aguiar, V. Martinez, J.J. Martinez-Murcia, F.J. Martínez-Tomás, R. Mekyska, J. Nalepa, G.J. Novais, P. Orellana, D. Ortiz, A. Palacios-Alonso, D. Palma, J. Pereira, A. Pinacho-Davidson, P. Pinninghoff, M.A. Ponticorvo, M. Psarrou, A. Ramírez, J. Rincón, M. Rodellar-Biarge, V. Rodríguez-Rodríguez, I. Roelofsma, P.H.M.P. Santos, J. Salas-Gonzalez, D. Salcedo-Lagos, P. Segovia, F. Shoeibi, A. Silva, M. Simic, D. Suckling, J. Treur, J. Tsanas, A. Varela, R. Wang, S.H. Wang, W. Zhang, Y.D. Zhu, H. Zhu, Z. Ferrández-Vicente, J.M. SiPBA at Data Science and Computational Intelligence Institute University of Granada Granada Spain University of Granada Granada Spain Dept. of Psychiatry University of Cambridge Cambridge United Kingdom Dept. of Communications Engineering University of Malaga Malaga Spain School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Semantic Information Systems Group Osnabrück University Osnabrück Germany Osnabrück Germany Dept. of Electronics Computer Technology and Projects Universidad Politécnica de Cartagena Cartagena Spain Universitat Politècnica de València València Spain Institute of Applied Computer Science Jagiellonian University Kraków Poland Dept. of Information and Communication Engineering University of Murcia Murcia Spain Dept. of Computer Science and Information Technologies University of A Coruña A Coruña Spain Dept. of Computer Science University of Oviedo Oviedo Spain Buenos Aires Argentina Buenos Aires Argentina Eindhoven University of Technology Eindhoven5612 AZ Netherlands Dept. of Computer Science University of Malaga Malaga Spain De Montfort University Leicester United Kingdom Dept. of Computer Science Faculty of Engineering Universidad de Concepción Concepción Chile Neurocognition and Emotion Research Unit Albacete Research Institute of Informatics University of Castilla-La Mancha Albacete Spain Dept. of Educational Informatics Universidad de Concepción Concepción Chile Madrid Spain Dept. of Humanistic Studies University of Naples Federico II Napoli Italy Escuela Técnica Superior de Ingeniería Informática Universidad Rey Juan Carlos Campus de Móstoles Móstoles Madrid28933 Spain Neuromorphic Speech Processing Lab Center for Biomedical Technology Universidad Politécnica de Madrid Campus de Montegancedo Pozuelo de Alarcón Madrid28223 Spain Biomedical Research Networking Center in Mental Health Instituto de Salud Carlos III Madrid28016 Spain Usher Institute Faculty o

Groundbreaking advances in theoretical and applied Artificial Intelligence (AI). DL algorithms are groundedin non-linear and complex artificial neural systems that progressively extract higher-level features from *** is frequently compared with human-level performance in real-world tasks, such as clinical diagnostics. Itis also a turning point in solving otherwise intractable problems in the design of virtual agents or robotics;orin providing novel insight into disease progress in genomics and Neuroimaging (NI), understanding humanbrain function, the automation of industrial processes based on computer vision, and so on. In this paper, themost relevant advances from the last few years in AI and several applications to neuroscience, neuroimaging,computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-ofthe-art in AI methods, models and applications within a collection of works presented at the 9th InternationalConference on the Interplay between Natural and Artificial Computation (IWINAC). The works presentedin this paper are excellent examples of new scientific discoveries made in laboratories that are successfullytransferred to real-life applications. © 2023, The Authors. All rights reserved.

关键词： Neuroimaging

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IEEE Workshop NEXTA 2021: The Next Level of Test Automation - Welcome Message

Proceedings - 2021 IEEE 14th International Conference on Sof...

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Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021 2021年 XIX页

作者： Eldh, Sigrid Garousi, Vahid Tahvili, Sahar Felderer, Michael Sandahl, Kristian Business Unit Networks Standards and Technology Software Computer Science Ericsson AB Stockholm Sweden School of EEECS Queen's University Belfast Bahar Software Engineering Consulting Corporation Belfast United Kingdom Group Function Technology Global AI Accelerator Ericsson AB Stockholm Sweden Dept. of Computer Science University of Insbruck Innsbrück Austria Dept. of Computer and Information Science Linköping University Linköping Sweden

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Enabling Conditions for the Deployment of Integrated Local Energy Communities in Europe

Enabling Conditions for the Deployment of Integrated Local E...

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Blockchain for Renewables Integration (BLORIN), Workshop on

作者： Martina Caliano Amedeo Buonanno Marialaura Di Somma Giorgio Graditi Christina Papadimitriou Chrysanthos Charalambous Przemysław Dopierała Leszek Bronk Dept. of Energy Technologies and Renewable Energy Sources ENEA Portici NA Italy Electrical Engineering dpt. Eindhoven University of Technology (TU/e) Eindhoven The Netherlands Department of Electrical and Computer Engineering University of Cyprus FOSS Research Centre for Sustainable Energy Nicosia Cyprus Department of Control Information and Communications Instytut Energetyki - Instytut Badawczy Gdansk Poland Department of Strategy and System Development Instytut Energetyki - Instytut Badawczy Gdansk Poland

ISBN: (纸本)9781665472500

The main goal of eNeuron H2020 project (Nov 2020-Oct. 2024, ID: 957779) is to develop innovative tools for the optimal design and operation of local energy communities, integrating distributed energy resources and multiple energy carriers at different scales. This paper presents a review study of the enabling conditions for the deployment of integrated local energy communities (ILECs) in Europe, performed within the project. The enabling conditions are addressed by defining the key actors and their interests in the implementation of an energy community at local level and through a detailed mapping of the enabling and emerging energy and information and communication technologies at both household and community levels. Special focus is also on mapping of the demand-side flexibility technologies to understand the benefits of local flexibility and impacts on the larger systems. In such analysis, the key issues for implementation and adaptation of this new energy paradigm are investigated through covering technological, socio-economic, environmental, and regulatory aspects.

关键词： Renewable energy sources Conferences Europe Information and communication technology Distributed power generation Blockchains

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Energy-efficient Dynamic Resource Allocation for Network Functions in Softwarization based networks

Energy-efficient Dynamic Resource Allocation for Network Fun...

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IEEE International Conference on communications (ICC)

作者： Mengjie Liu Gang Feng Shuang Qin Weihua Zhuang National Key Lab. on Communications University of Electronic Science and Technology of China Dept. of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Driven by an explosive increase in the number of users and data usage, energy consumption becomes a significant concern for information and communication technology industry. In softwarization based networks, energy-efficient Network Function (NF) resource allocation is imperative yet challenging for service provisioning. In this paper, we investigate dynamic NF resource allocation (NFRA) problem for service function chains (SFCs) with aim to minimize the long-term energy consumption, while guaranteeing the end-to-end delay requirements for the packets traversing the SFCs. We formulate the problem as an infinite horizon Markov Decision Process (MDP) problem and obtain the global optimal solution based on the value iteration algorithm which has high computational complexity. The global optimal solution serves as a performance upper bound due to its high computational complexity. To cater for efficient on-line NFRA decisions, we further design a suboptimal distributed value iteration based dynamic NF resource allocation (DDRA) algorithm. The numerical results based on real-world data traces demonstrate the proposed DDRA algorithm achieves a close-to-optimal performance and a significant performance improvement compared with two known NF resource allocation algorithms.

关键词： Switches Substrates Quality of service Energy resources Noise measurement

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Robust Network Flow Classification against Malicious Feature Manipulation

Robust Network Flow Classification against Malicious Feature...

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IEEE International Conference on communications (ICC)

作者： Yupeng Li Ben Liang Ali Tizghadam Dept. of Electrical and Computer Engineering University of Toronto Toronto Canada Technology Strategy and Business Transformation TELUS Communications Toronto Canada

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Network flow classification is essential to proper provisioning of Quality of Service (QoS). Conventional machine-learning based flow classification methods assume reliable knowledge of the flow features. However, in practice, malicious flow generators can manipulate the flow features to increase the likelihood of certain learning outcomes, e.g., in terms of the QoS requirement label. Training a classifier that is robust to such feature manipulation is imperative. In this work, we present a study on robust flow classification against malicious feature manipulation. We leverage a detailed system model to capture the relation between the classifier and malicious flow generators and propose a Stackelberggame based solution framework to train a robust classifier. We conduct extensive experimentation using real-world traces. For flows with manipulated features, the Stackelberg classifier trained by our solution framework significantly outperforms a non-robust classifier that is oblivious to manipulation, achieving accuracy close to that of the non-robust classifier on unmanipulated flows. Furthermore, the Stackelberg classifier on manipulated test flows is no worse than the non-robust classifier on unmanipulated flows.

关键词： Generators Robustness Games Quality of service Training Machine learning Training data

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Optical data transmissionwith high spectral efficiency at44Terabits/s with a soliton crystal micro-comb

Optical data transmissionwith high spectral efficiency at44T...

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Signal Processing in Photonic communications, SPPCom 2021 - Part of OSA Advanced Photonics Congress 2021

作者： Tan, M. Corcoran, B. Xu, X. Wu, J. Boes, A. Nguyen, T. Chu, S. Little, B. Morandotti, R. Mitchell, A. Moss, D.J. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Dept. of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering Rmit University MelbourneVIC3001 Australia Department of Physics and Material Science City University of Hong Kong Tat Chee Avenue Hong Kong Xi'an Institute of Optics and Precision Mechanics Precision Mechanics of Cas Xi'an China INRS-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology Chengdu China

We report data transmission over 75km in the lab and a field trial, at 44.2 Tb/s over standard optical fibre using a single integrated chip source, reaching a spectral efficiency of 10.4 bits/s/Hz. © 2021 OSA - T...

ISBN: (纸本)9781557528209

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