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Modeling, Capacity Studies, Antenna and System Designs for 6G/B6G 3D Continuous-Space Radio Channels Enabled by Electromagnetic Information Theory

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IEEE Communications Surveys and Tutorials 2025年

作者： Wang, Cheng-Xiang Li, Junling Huang, Jie Huang, Chen Zhang, Zhaoyang Liu, Ying Zhou, Shidong Chen, Yunfei You, Xiaohu Gao, Xiqi Cui, Tie Jun Renzo, Marco Di Thompson, John Haas, Harald Schober, Robert Zhang, Rui Southeast University National Mobile Communications Research Laboratory School of Information Science and Engineering Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Zhejiang University Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking College of Information Science and Electronic Engineering Hangzhou310007 China Xidian University National Key Laboratory of Radar Detection and Sensing Xi'an710071 China Tsinghua University State Key Laboratory on Microwave and Digital Communications Beijing100084 China University of Durham Department of Engineering DurhamDH1 3LE United Kingdom Southeast University State Key Laboratory of Millimeter Waves School of Information Science and Engineering Nanjing211189 China UniversitèParis-Saclay Laboratoire des Signaux et Systèmes CNRS CentraleSupélec Gif-sur-Yvette91192 France Centre for Telecommunications Research - Department of Engineering King's College London LondonWC2R 2LS United Kingdom School of Engineering EdinburghEH9 3BF United Kingdom Cambridge University Department of Engineering CambridgeCB2 1PZ United Kingdom Institute for Digital Communications Erlangen91054 Germany The Chinese University of HongKong School of Science and Engineering Shenzhen Research Institute of Big Data Shenzhen518172 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

Channel theory is a fundamental theory of wireless communications. The sixth generation (6G) and beyond 6G (B6G) wireless communication networks are expected to provide space-air-ground-sea global coverage. Base stations and users tend to move in three dimensional (3D) continuous spaces, while antennas and propagation environments can be tightly coupled. The underlying channels show an evolutionary trend to 3D continuous-space radio channels that combine antennas and wireless propagation channels, in comparison to discrete local-space wireless propagation channels in previous generations. This introduces new challenges for channel modeling, channel capacity analysis, antenna design, system design, etc. To address these challenges, this paper performs a comprehensive study on 3D continuous-space radio channels in 6G/B6G with the aid of electromagnetic information theory (EIT) that integrates electromagnetic theory, information theory, wireless propagation channel modeling theory, and antenna theory. We start by revealing the connections and gaps between these four fundamental theories. Then, an in-depth investigation on the four major research thrusts of 3D continuous-space radio channels is provided: 1) channel measurements and modeling, 2) channel capacity analysis, 3) general antenna design, and 4) wireless system design. We aim to explore the intrinsic relationships between antenna parameters, channel parameters, channel characteristics, channel capacity, and communication system performance. Finally, future research directions and challenges for 3D continuous-space radio channels are outlined. Our study endeavors to establish a fundamental framework for 3D continuous-space radio channels, with the potential to catalyze breakthroughs in 6G/B6G theories. © 1998-2012 IEEE.

关键词： Antenna grounds

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All-optical measurement-device-free feedforward enabling ultra-fast quantum informationprocessing

arXiv

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arXiv 2024年

作者： Yamashima, Taichi Kashiwazaki, Takahiro Suzuki, Takumi Nehra, Rajveer Nakamura, Tomohiro Inoue, Asuka Umeki, Takeshi Takase, Kan Asavanant, Warit Endo, Mamoru Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Atsugi Kanagawa243-0198 Japan Department of Electrical and Computer Engineering University of Massachusetts Amherst AmherstMA01003 United States Department of Physics University of Massachusetts Amherst AmherstMA01003 United States College of Information and Computer Science University of Massachusetts Amherst AmherstMA01003 United States Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Wako Saitama351-0198 Japan

Utilizing feedforward to perform adaptive quantum operations on one entangled state according to the measurement result of the other state enables measurement-based quantum information processing (QIP). Until now, the bandwidth of feedforward in optical QIP has been limited to around 100 MHz by measurement with electronics. A potential alternative is the utilization of an optical parametric amplifier (OPA). This optical device eliminates the need for electronic measuring devices and enables all-optical broadband feedforward. In this paper, we demonstrate a variable squeezing gate with an operation bandwidth of 1.3 THz by all-optical measurement-device-free feedforward. We utilize a periodically poled lithium niobate waveguide as a broadband OPA and perform continuous phase locking in our optical system. Experimental results demonstrate that our all-optical QIP operates at a THz clock frequency, representing a major step toward the realization of an ultra-fast quantum computer. © 2024, CC BY.

关键词： Parametric amplifiers

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Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemble

arXiv

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arXiv 2024年

作者： Chen, Chuangtao Zhao, Qinglin Zhou, MengChu He, Zhimin Sun, Zhili Situ, Haozhen Faculty of Innovation Engineering Macau University of Science and Technology Macao999078 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States School of Electronic and Information Engineering Foshan University Foshan528000 China Institute of Communication Systems University of Surrey GuildfordGU2 7XH United Kingdom College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

Classical diffusion models have shown superior generative results. Exploring them in the quantum domain can advance the field of quantum generative learning. This work introduces Quantum Generative Diffusion Model (QGDM) as their simple and elegant quantum counterpart. Through a non-unitary forward process, any target quantum state can be transformed into a completely mixed state that has the highest entropy and maximum uncertainty about the system. A trainable backward process is used to recover the former from the latter. The design requirements for its backward process includes non-unitarity and small parameter count. We introduce partial trace operations to enforce non-unitary and reduce the number of trainable parameters by using a parameter-sharing strategy and incorporating temporal information as an input in the backward process. We present QGDM’s resource-efficient version to reduce auxiliary qubits while preserving generative capabilities. QGDM exhibits faster convergence than Quantum Generative Adversarial Network (QGAN) because its adopted convex-based optimization can result in better convergence. The results of comparing it with QGAN demonstrate its effectiveness in generating both pure and mixed quantum states. It can achieve 53.02% higher fidelity in mixed-state generation than QGAN. The results highlight its great potential to tackle challenging quantum generation tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Development of an Automotive Climate Control System for Low-End Vehicles in Tropical Climate Environment

SSRN

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SSRN 2023年

作者： Ahmad, M.A. Yakub, Fitri Othman, N.A. Kadir, K.W. Rashid, M.Z.A. Manan, K.E. Mas, M.R.H. Omar Ainaa, Z. Hanis Sinha, V.K. Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Hang Tuah Jaya Melaka Durian Tunggal76100 Malaysia Garisan Industries Sdn. Bhd. No. 3a Tingkat 1 Jalan Wawasan Ampang 2/2 Ampang Selangor68000 Malaysia Department of Computer Science & Engineering Chitkara University Himachal Pradesh 174103 India

In past decades, researchers have given much attention towards the development of a novel and improved heating, ventilation, and air-conditioning (HVAC) system in a vehicle. HVAC system is known to provide a comfortable vehicular environmental for occupants by regulating the cabin’s temperature and humidity, improving the overall indoor air quality. With the emergence of electric and hybrid electric vehicles for future car markets, the prospect of an energy efficient HVAC system is very critical and demanding to avoid energy wastage by battery powered vehicles. While HVAC systems improve the thermal comfort of a vehicle's interior, it also increases the vehicle's energy consumption. The objective of this study is to develop a novel HVAC system by automating the automotive climate control system (ACCS) that minimize the energy consumption of a vehicle's HVAC system while preserving thermal comfort. This proposed control method is basically inspired for the use of low-end vehicles due to its simplicity and acceptable efficiency in performance. A simulation of the proposed ACCS is performed to show the system's ability in optimization of its energy. © 2023, The Authors. All rights reserved.

关键词： Thermal comfort

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Beyond Strang: A practical assessment of some second-order 3-splitting methods

arXiv

引用

arXiv 2023年

作者： Spiteri, Raymond J. Tavassoli, Arash Wei, Siqi Smolyakov, Andrei Department of Computer Science University of Saskatchewan 110 Science Place SaskatoonSKS7N 5K9 Canada Department of Mathematics and Statistics University of Saskatchewan 106 Wiggins Road SaskatoonSKS7N 5E6 Canada Department of Physics and Engineering Physics University of Saskatchewan 116 Science Place SaskatoonSKS7N 5E2 Canada

Operator splitting is a popular divide-and-conquer strategy for solving differential equations. Typically, the right-hand side of the differential equation is split into a number of parts that are then integrated separately. Many methods are known that split the right-hand side into two parts. This approach is limiting, however, and there are situations when 3-splitting is more natural and ultimately more advantageous. The second-order Strang operator-splitting method readily generalizes to a right-hand side splitting into any number of operators. It is arguably the most popular method for 3-splitting because of its efficiency, ease of implementation, and intuitive nature. Other 3-splitting methods exist, but they are less well-known, and analysis and evaluation of their performance in practice are scarce. We demonstrate the effectiveness of some alternative 3-split, second-order methods to Strang splitting on two problems: the reaction-diffusion Brusselator, which can be split into three parts that each have closed-form solutions, and the kinetic Vlasov-Poisson equations that is used in semi-Lagrangian plasma simulations. We find alternative second-order 3-operator-splitting methods that realize efficiency gains of 10%-20% over traditional Strang splitting. Our analysis for the practical assessment of efficiency of operator-splitting methods includes the computational cost of the integrators and can be used in method design. © 2023, CC BY-NC-ND.

关键词： Efficiency

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Robustness of Online Proportional Response in Stochastic Online Fisher Markets: a Decentralized Approach

arXiv

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arXiv 2024年

作者： Yang, Yongge Lee, Yu-Ching Chen, Po-An Lin, Chuang-Chieh Economics and Management School Wuhan University Hubei Wuhan China Department of Industrial Engineering National Tsing Hua University 101 Sec 2 Kuang-Fu Rd Hsinchu City300 Taiwan Institute of Information Management National Yang Ming Chiao Tung University 1001 University Rd Hsinchu City300 Taiwan Department of Computer Science and Information Engineering Tamkang University 151 Yingzhuan Rd New Taipei City251301 Taiwan

Problem Definition: This study is focused on periodic Fisher markets where items with time-dependent and stochastic values are regularly replenished and buyers aim to maximize their utilities by spending budgets on these items. Traditional approaches of finding a market equilibrium in the single-period Fisher market rely on complete information about buyers’ utility functions and budgets. However, it is impractical to consistently enforce buyers to disclose this private information in a periodic setting. Methodology/results: We introduce a distributed auction algorithm, online proportional response, wherein buyers update bids solely based on the randomly fluctuating values of items in each period. The market then allocates items based on the bids provided by the buyers. We show connections between the online proportional response and the online mirror descent algorithm. Utilizing the known Shmyrev convex program, a variant of the Eisenberg-Gale convex program that establishes market equilibrium of a Fisher market, two performance metrics are proposed: the fairness regret is the cumulative difference in the objective value of a stochastic Shmyrev convex program between an online algorithm and an offline optimum, and the individual buyer’s regret gauges the deviation in terms of utility for each buyer between the online algorithm and the offline optimum. Our algorithm attains a problem-dependent upper bound in fairness regret under stationary inputs. This bound is contingent on the number of items and buyers. Additionally, we conduct analysis of regret under various non-stationary stochastic input models to demonstrate the algorithm’s efficiency across diverse scenarios. Managerial implications: The online proportional response algorithm addresses privacy concerns by allowing buyers to update bids without revealing sensitive information and ensures decentralized decision-making, fostering autonomy and potential improvements in buyer satisfaction. Furthermore, our algo

关键词： Stochastic systems

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A Novel Approach for Fake Comments and Reviews Detection on the Online Social Networks

A Novel Approach for Fake Comments and Reviews Detection on ...

引用

2021 International Conference on Smart Systems and Advanced Computing, SysCom 2021

作者： Gaurav, Akshat Gupta, B.B. Chui, Kwok Tai Peraković, Dragan Chaurasia, Priyanka Hsu, Ching-Hsien Ronin Institute MontclairNJ07043 United States National Institute of Technology Kurukshetra Haryana Kurukshetra136119 India Asia University Taichung413 Taiwan Staffordshire University Stoke-on-TrentST4 2DE United Kingdom Hong Kong University of Zagreb Croatia Ulster University Magee campus Londonderry United Kingdom Department of Computer Science and Information Engineering Asia University Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Department of Medical Research China Medical University Hospital China Medical University Taiwan

As the primary source of information dissemination, social media networks have surpassed traditional news organisations for the first time. Nonetheless, as the number of people who use social media websites grows, they become more susceptible to the spread of misinformation, making it increasingly difficult to distinguish between real news and false news in real time. In this paper, we proposed a machine learning technique for the detection of fake comments in social networks. According to the results of the experiment, it is clear that the machine learning technique efficiently detects the fake comments. © 2021 Copyright for this paper by its authors.

关键词： Information dissemination

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Threshold Study for Hanzi Image Recognition: Defining Character and Component Limits in Chinese, Japanese, and Korean Script Processing

International Journal of Asian Language Processing

引用

International Journal of Asian Language Processing 2025年第1期35卷

作者： Weigang Li Rafael Marconi Ramos Pedro Carvalho Brom Danilo Lelin Li Department of Computer Science University of Brasilia Brasilia CEP 70910-900 Brazil Department of Electronic and Electrical Engineering Trinity College Dublin Dublin 2 Ireland

Chinese, Japanese, and Korean (CJK) Hanzi image recognition still faces significant challenges, particularly with pixel resolution, stroke count, character frequency and structure. This paper introduces the concepts of character and component thresholds to establish foundational parameters for Hanzi recognition, considering Unevenly Distributed Composite Character (UDCC), which account for up to 88% of Chinese characters. We compiled corpora of Simplified, Traditional characters, and Japanese Kanji, analyzing 3395 images with stroke counts ranging from 1 to 64, and developed the ZH-TC-IM965858 database, containing 33,950 images across 10 pixel resolutions. Using Euclidean distance and ResNet50 similarity analysis, we identified a character threshold of 26 strokes for 24×24 pixel images, a component threshold of 14 strokes, and a comprehensive threshold of 16 strokes. We found that 7.61% of 8105 common Chinese characters, 27.41% of 96,585 Traditional characters, and 5.99% of 2163 Japanese Kanji exceed this comprehensive threshold. Character Length and Character Frequency (CLCF) models were employed to explore relationships between stroke count, frequency, and thresholds. Additionally, Scale-invariant Feature Transform (SIFT) was applied to match radicals and components, providing insights for improving recognition accuracy. This research advances Hanzi image recognition and enhances multimodal Large Language Models (LLMs) for ideographic languages.

关键词： CJK Hanzi Image Recognition Multi-modal NLP SIFT Threshold

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Towards a rigorous evaluation of explainability for multivariate time series

arXiv

引用

arXiv 2021年

作者： Saluja, Rohit Malhi, Avleen Knapič, Samanta Främling, Kary Cavdar, Cicek Department of Computer Science Aalto University Konemiehentie 2 Espoo02150 Finland Department of Computing Science Umeå University Mit-huset Umeå90187 Sweden Department of Computing and Informatics Bournemouth United Kingdom Department of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Machine learning-based systems are rapidly gaining popularity and in-line with that there has been a huge research surge in the field of explainability to ensure that machine learning models are reliable, fair, and can be held liable for their decision-making process. Explainable Artificial Intelligence (XAI) methods are typically deployed to debug black-box machine learning models but in comparison to tabular, text, and image data, explainability in time series is still relatively unexplored. The aim of this study was to achieve and evaluate model agnostic explainability in a time series forecasting problem. This work focused on proving a solution for a digital consultancy company aiming to find a data-driven approach in order to understand the effect of their sales related activities on the sales deals closed. The solution involved framing the problem as a time series forecasting problem to predict the sales deals and the explainability was achieved using two novel model agnostic explainability techniques, Local explainable model- agnostic explanations (LIME) and Shapley additive explanations (SHAP) which were evaluated using human evaluation of explainability. The results clearly indicate that the explanations produced by LIME and SHAP greatly helped lay humans in understanding the predictions made by the machine learning model. The presented work can easily be extended to any time series forecasting or classification scenario for achieving explainability and evaluating the produced explanations. © 2021, CC BY-SA.

关键词： Forecasting

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DDPG-E2E: A Novel Policy Gradient Approach for End-to-End Communication Systems

arXiv

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arXiv 2024年

作者： Zhang, Bolun Van Huynh, Nguyen Hoang, Dinh Thai Nguyen, Diep N. Pham, Quoc-Viet The School of Engineering University of Warwick CoventryCV4 7AL United Kingdom The Department of Electrical Engineering and Electronics University of Liverpool LiverpoolL69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney SydneyNSW2007 Australia The School of Computer Science and Statistics Trinity College Dublin The University of Dublin Dublin 2D02 PN40 Ireland

The End-to-end (E2E) learning-based approach has great potential to reshape the existing communication systems by replacing the transceivers with deep neural networks. To this end, the E2E learning approach needs to assume the availability of prior channel information to mathematically formulate a differentiable channel layer for the back-propagation (BP) of the error gradients, thereby jointly optimizing the transmitter and the receiver. However, accurate and instantaneous channel state information is hardly obtained in practical wireless communication scenarios. Moreover, the existing E2E learning-based solutions exhibit limited performance in data transmissions with large block lengths. In this article, these practical issues are addressed by our proposed deep deterministic policy gradient-based E2E communication system. In particular, the proposed solution utilizes a reward feedback mechanism to train both the transmitter and the receiver, which alleviates the information loss of error gradients during BP. In addition, a convolutional neural network-based architecture is developed to mitigate the curse of dimensionality problem when transmitting messages with large block lengths. Extensive simulations then demonstrate that our proposed solution can not only jointly train the transmitter and the receiver simultaneously without requiring prior channel knowledge but also can obtain significant performance improvement compared to state-of-the-art solutions. © 2024, CC BY-NC-ND.

关键词： Convolutional neural networks

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