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arXiv 2024年

作者： Lai, Xiazhi Yao, Junteng Zhi, Kangda Wu, Tuo Morales-Jimenez, David Wong, Kai-Kit The School of Computer Science Guangdong University of Education Guangdong Guangzhou China The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Signal Theory Networking and Communications Universidad de Granada Granada18071 Spain The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The Yonsei Frontier Laboratory The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of

In this correspondence, we analyze the performance of a reconfigurable intelligent surface (RIS)-aided communication system that involves a fluid antenna system (FAS)-enabled receiver. By applying the central limit theorem (CLT), we derive approximate expressions for the system outage probability when the RIS has a large number of elements. Also, we adopt the block-correlation channel model to simplify the outage probability expressions, reducing the computational complexity and shedding light on the impact of the number of ports. Numerical results validate the effectiveness of our analysis, especially in scenarios with a large number of RIS elements. © 2024, CC BY.

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Novel Personalized Multimedia Recommendation Systems Using Tensor Singular-Value-Decomposition

Novel Personalized Multimedia Recommendation Systems Using T...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Shih Yu Chang Hsiao-Chun Wu Kun Yan Xinjia Chen Yiyan Wu Department of Applied Data Science San Jose State University San Jose CA USA School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge LA USA Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin China Department of Information and Telecommunication Guilin University of Electronic Technology Guilin China Department of Engineering Technology Northwestern State University of Louisiana Natchitoches LA USA Communications Research Centre Canada Ottawa ON Canada

Nowadays, multimedia data are often produced by various sources, e.g., Internet of Things (IoT), social media, customer databases, etc. As tremendous multimedia data are produced every day, users or E-commerce customers cannot infer information from such data by themselves and therefore recommender systems have been developed to help users to select the products or services which better fit users’ preferences or requirements. Nonetheless, there exists few works on the incorporation of side information or multiple attributes about items into the design of a more robust recommender system. In this work, we propose a novel approach based on the third-order tensor singular-value-decomposition (T3-SVD) to design new personalized multimedia recommender systems (PMRSs) for internet users. A PMRS can dynamically adjust its recommendation strategy subject to a particular user’s on-line transaction behavior. To evaluate the effectiveness of our proposed PMRS based on T3-SVD, we compare the performances of our proposed new PMRS and two other existing tensor-based recommendation systems over realworld data in terms of normalized root-mean-square error (NRMSE). As a result, our proposed new PMRS greatly outperforms the other two existing systems.

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Hybrid-Field Channel Estimation for Massive MIMO Systems based on OMP Cascaded Convolutional Autoencoder

Hybrid-Field Channel Estimation for Massive MIMO Systems bas...

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IEEE Conference on Vehicular Technology (VTC)

作者： Hasan Nayir Erhan Karakoca Ali Görçin Khalid Qaraqe Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Department of Electronics and Communication Engineering Istanbul Technical University İstanbul Turkey Communications and Signal Processing Research (HİSAR) Lab. TÜBİTAK BİLGEM Kocaeli Turkey Department of Electronics and Communication Engineering Yildiz Technical University İstanbul Turkey

ISBN: (纸本)9781665454698

Frequency scarcity implies the utilization of higher frequencies for wireless communications; however, spreading loss becomes a dominating issue as the frequency increases to the level of and beyond millimeter waves. To this end, massive multiple-input multiple-output structures introduce mitigation alternatives. However, to make these solutions possible, the channel estimation approach strives to be modified: since Rayleigh distance is very short for conventional systems, the only far-field channel is examined in that context. On the other hand, the implementation of massive antenna arrays in high frequencies increases Rayleigh distance; thus, both near-field and far-field analyses become necessary. Instead of a dual estimation process, it would be effective and efficient to develop hybrid-field channel estimation techniques. Therefore, in this study, a new channel estimation method which is based on convolutional autoencoder (CAE) and orthogonal matching pursuit (OMP) approach, is proposed for hybrid channel estimation. The results indicate that the proposed OMP-CAE method has much better error performance when compared to the conventional OMP algorithm, especially at low signal-to-noise ratio regimes.

关键词： Wireless communication Vehicular and wireless technologies Convolution Simulation Channel estimation Matching pursuit algorithms Ray tracing

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Semantic communications:Theories,Technologies and Applications

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中国通信（英文版） 2024年第7期21卷前插1-前插5页

作者： Zhang Ping Shi Guangming Cui Shuguang Zhang Zhaoyang Niu Kai Xiao Yong Qin Zhijin Dai Jincheng Shao Shuo Deniz Gündüz Eleonora Grassucci School of Information and Communication Engineering at Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology IMT-2020(5G)Experts Panel Experts Panel for China's 6G development Peng Cheng Laboratory School of Artifi-cial Intelligence Xidian University electrical and computer engineering with the University of Arizona Texas A&M University UC Davis Chinese Univer-sity of Hong Kong(Shenzhen)(CUHK-Shenzhen) Zhejiang University School of Artificial Intelli-gence BUPT School of Electron-ic Information and Communications at the Huazhong University of Science and Technology(HUST) WuhanChina Peng Cheng Laboratory Guang-zhouChina and the Pazhou Laboratory(Huangpu)Guang-zhouChina Tsinghua University BeijingChina Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and Telecommunications School of Electronics Informa-tion and Electrical EngineeringShanghai Jiao Tong Univer-sityChina Information Processing in the Electrical and Electronic Engineering Department at Imperial College London UK Intelligent Systems and Networks Group Department at Imperial College London UK Department of Information Engineering Electronicsand Telecommunications of the Sapienza University of Rome

The last seventy years have witnessed the transi-tion of communication from Shannon's theoretical concept to current high-efficiency practical *** respect to Shannon information theory,to fulfill the high-bandwidth utilization,any further increase in the data rate requires a significant augmentation in the received signal power unless the bandwidth is extended in proportion to the incre-mental data rate.

关键词： Special issues and sections Semantics Communication systems Data processing Information theory Data augmentation

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Fluid Antennas-Enabled Multiuser Uplink: A Low-Complexity Gradient Descent for Total Transmit Power Minimization

arXiv

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arXiv 2023年

作者： Hu, Guojie Wu, Qingqing Xu, Kui Ouyang, Jian Si, Jiangbo Cai, Yunlong Al-Dhahir, Naofal The College of Communication Engineering Rocket Force University of Engineering Xi’an710025 China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China The College of Communications Engineering The Army of Engineering University Nanjing210007 China The Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Nanjing210003 China The Integrated Service Networks Lab of Xidian University Xi’an710100 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

We investigate multiuser uplink communications from multiple single-antenna users to a base station (BS), which is equipped with multiple fluid antennas (FAs) and adopts zero-forcing receivers to decode multiple signals. We aim to optimize antennas’ positions at the BS, to minimize the total transmit power of all users subject to the minimum rate requirement. After applying transformations, we show that the problem is equivalent to minimizing the sum of each eigenvalue’s reciprocal of a matrix, which is a function of all antennas’ positions at the BS. Subsequently, the projected gradient descent (PGD) method is utilized to find a locally optimal solution. In particular, different from the latest related work, we exploit the eigenvalue decomposition to successfully derive a closed-form gradient for the PGD, which facilitates the practical implementation greatly. We demonstrate by simulations that via careful optimization for all antennas’ positions in our proposed design, the total transmit power of all users can be decreased significantly as compared to competitive benchmarks. Copyright © 2023, The Authors. All rights reserved.

关键词： Antennas

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Data Fusion for Multipath-Based SLAM: Combining Information from Multiple Propagation Paths

arXiv

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arXiv 2022年

作者： Leitinger, Erik Venus, Alexander Teague, Bryan Meyer, Florian The Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria The Christian Doppler Laboratory for Location-aware Electronic Systems Austria The MIT Lincoln Laboratory LexingtonMA United States The Department of Electrical and Computer Engineering and Scripps Institution of Oceanography University of California San Diego San DiegoCA United States

Multipath-based simultaneous localization and mapping (SLAM) is an emerging paradigm for accurate indoor localization constrained by limited navigation resources. The goal of multipath-based SLAM is to support the estimation of time-varying positions of mobile agents by detecting and localizing radio-reflective surfaces in the environment. In existing Bayesian methods, a propagation surface is represented by the mirror image of each physical anchor (PA) across that surface – known as the corresponding "virtual anchor" (VA). Due to this VAs representation, each propagation path is mapped individually. Existing methods thus neglect inherent geometrical constraints across different paths that interact with the same surface, which limits accuracy and speed. In this paper, we introduce an improved statistical model and estimation method that enables data fusion in multipath-based SLAM. By directly representing each surface with a master virtual anchor (MVA), geometrical constraints across propagation paths are also modeled statistically. A key aspect of the proposed method based on MVAs is to check the availability of single-bounce and double-bounce propagation paths at potential agent positions by means of ray-tracing (RT). This availability check is directly integrated into the statistical model as detection probabilities for propagation paths. Estimation is performed by a sum-product algorithm (SPA) derived based on the factor graph that represents the new statistical model. Numerical results based on simulated and real data demonstrate significant improvements in estimation accuracy compared to state-of-the-art multipath-based SLAM methods. © 2022, CC BY.

关键词： Mobile agents

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Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks

arXiv

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arXiv 2021年

作者： Théate, Thibaut Wehenkel, Antoine Bolland, Adrien Louppe, Gilles Ernst, Damien Department of Electrical Engineering and Computer Science University of Liège Liège Belgium Information Processing and Communications Laboratory Institut Polytechnique de Paris Paris France

The distributional reinforcement learning (RL) approach advocates for representing the complete probability distribution of the random return instead of only modelling its expectation. A distributional RL algorithm may be characterised by two main components, namely the representation of the distribution together with its parameterisation and the probability metric defining the loss. The present research work considers the unconstrained monotonic neural network (UMNN) architecture, a universal approximator of continuous monotonic functions which is particularly well suited for modelling different representations of a distribution. This property enables the efficient decoupling of the effect of the function approximator class from that of the probability metric. The research paper firstly introduces a methodology for learning different representations of the random return distribution (PDF, CDF and QF). Secondly, a novel distributional RL algorithm named unconstrained monotonic deep Q-network (UMDQN) is presented. To the authors’ knowledge, it is the first distributional RL method supporting the learning of three, valid and continuous representations of the random return distribution. Lastly, in light of this new algorithm, an empirical comparison is performed between three probability quasi-metrics, namely the Kullback-Leibler divergence, Cramer distance, and Wasserstein distance. The results highlight the main strengths and weaknesses associated with each probability metric together with an important limitation of the Wasserstein distance. Copyright © 2021, The Authors. All rights reserved.

关键词： Reinforcement learning

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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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Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

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IFAC-PapersOnLine 2022年第6期55卷 127-132页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Science and Technology of Kasserine University of Kairouan PO Box 471 1200 Kasserine Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

This work proposes a new fault diagnosis approach for a wind energy conversion (WEC) system. The proposed technique merges the benefits of feature extraction based on Gaussian Process Regression (GPR) and Multi-Class Random Forest (MCRF)-based fault classification where instances are classified into one or more classes. In the developed GPR-MCRF approach, the nonlinear statistical features including the mean vector M GPR and the variance matrix C GPR are computed using the GPR model with aim of extracting the most relevant features from the WEC system. Then, these features are introduced to the RF classifier for classification and diagnosis purposes. Therefore, the application of the GPR-MCRF technique for WEC systems aims to enhance the use of the classical raw data-based MCRF and diagnosis accuracy. Three kinds of faults (wear-out, open-circuit, and short-circuit faults) are considered in this work. Different case studies are investigated in order to illustrate the effectiveness and robustness of the developed technique compared to the state-of-the-art methods. The obtained results show that the the developed GPR-MCRF technique is an effective feature extraction and fault diagnosis technique for WEC systems.

关键词： Random Forest (RF) Multi-Class Gaussian Process Regression (GPR) Fault Diagnosis Wind Energy Conversion Systems

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Variability in Spread Spectrum Time Domain Reflection and Transmission Measurements

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Makin, Samuel Addad, Mouad Redhead, Brent Furse, Cynthia M. University of Utah Electrical and Computer Engineering Department Salt Lake City 84112 UT United States Djillali Liabes University of Sidi Bel Abbes Telecommunications and Digital Signal Processing Laboratory SBA Algeria

Spread Spectrum Time Domain Reflectometry (SSTDR) offers a new non-intrusive measurement technique for microwave imaging. While vector network analyzers (VNAs) are conventional tools in this domain, they present significant drawbacks such as high cost and lengthy scan times. This paper explores the viability of substituting SSTDR devices for the VNA by validating their accuracy in comparison to traditional VNAs in the 0.5-4 GHz band. We conducted several tests of reflection and transmission measurements of RC loads, analysis of variations due to cable movement, calibration consistency, and temperature-induced variations. We also measured antenna S11 and S21 in two oil-based phantoms to simulate human breast tissue, comparing changes with the insertion of a metal tumor substitute. We found the mean confidence intervals of the VNA and SSTDR are better (less) than 0.03 for the |S11| and 0.02 for the |S21| from 0.5-4 GHz, and that metal “tumors” in the oil are detectable. These results suggest that SSTDR may be a viable alternative to VNAs for applications such as microwave breast imaging, warranting further investigation in more robust setups.

关键词： antenna measurements reflectometry spread spectrum time domain reflectometry (SSTDR) variability

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