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Variational Bayesian Learning based Joint Localization and Channel Parameter Estimation in Wireless Sensor Networks with Distance-dependent Noise

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IEEE Transactions on Vehicular Technology 2024年第5期74卷 6877-6891页

作者： Li, Yunfei Luo, Yiting Tan, Weiqiang Li, Chunguo Ma, Shaodan Yang, Guanghua Anhui Polytechnic University Department of Electrical Engineering Wuhu China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou China Southeast University School of Information Science and Engineering Nanjing China Purple Mountain Laboratories Nanjing China University of Macau State Key Lab. of Internet of Things for Smart City and the Dept. of Elec. and Computer Engineering Taipa China Jinan University School of Intelligent Systems Science and Engineering Zhuhai519070 China

This paper focuses on the challenge of jointly optimizing location and path loss exponent (PLE) in distancedependent noise. Departing from the conventional independent noise model used in localization and path loss exponent estimation problems, we consider a more realistic model incorporating distance-dependent noise variance, as revealed in recent theoretical analyses and experimental results. The distance-dependent noise introduces a complex noise model with unknown noise power and PLE, resulting in an exceptionally challenging nonconvex and nonlinear optimization problem. In this study, we address a joint localization and path loss exponent estimation problem encompassing distance-dependent noise, unknown parameters, and uncertainties in sensor node locations. To surmount the intractable nonlinear and non-convex objective function inherent in the problem, we introduce a variational Bayesian learning-based framework that enables the joint optimization of localization, path loss exponent, and reference noise parameters by leveraging an effective approximation to the true posterior distribution. Furthermore, the proposed joint learning algorithm provides an iterative closed-form solution and exhibits superior performance in terms of computational complexity compared to existing algorithms. computer simulation results demonstrate that the proposed algorithm approaches the performance of the Bayesian Cramer-Rao bound (BCRB), achieves localization performance comparable to the (maximum likelihood-Gaussian message passing) ML-GMP algorithm in some cases, and outperforms the other comparison algorithm in all cases. © 1967-2012 IEEE.

关键词： Iterative methods

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Quantum dot coherent comb lasers for B5G/6G mobile and terrestrial communication systems 28

Quantum dot coherent comb lasers for B5G/6G mobile and terre...

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Integrated Optics: Devices, Materials, and Technologies XXVIII 2024

作者： Lu, Z.G. Liu, G.C. Liu, J.R. Poole, P.J. Mao, Y.X. Zeb, K. Xie, X.R. Rahim, M. Vachon, M. Song, C.Y. Qi, Y. Weber, J. Barrios, P. Poitras, D. Sabourin, N. Chen, S. Zhao, P. Huang, L. Askarian, A. Zhang, X.P. Yao, J.P. Wu, K. Advanced Elec. and Photonics Research Centre National Research Council OttawaON Canada Depart. Electrical and Computer Engineering Concordia University MontrealQC Canada School of Elec. Engineering and Computer Science University of Ottawa OttawaON Canada Department of Electrical Engineering Ecole Polytechnique Montreal MontrealQC Canada

ISBN: (纸本)9781510670389

Future mobile and terrestrial communication systems B5G/6G are strongly expected to heterogeneously realize typically diversified performances, i.e. high-data-rate, high-mobility, low-latency, high-capacity, massive-connectivity and low-energy in order to satisfy the highly diversified application requirements. To achieve those goals the operation band of B5G/6G should be primarily in the millimeter-wave (mmW) range. Generation and distribution of mmW with traditional methods is limited by electronic bottleneck and associated complexity. Consequently broad bandwidth, simple, efficient, and cost-effective photonic mmW-over-fiber (mmWoF) transmission systems are solutions for B5G/6G. The spectral purity of mmW carriers is necessary. Numerous approaches have been proposed to generate pure mmW signals. Compared with other technologies, quantum dash or dot (QD) coherent comb lasers (QD CCLs) have great advantages for mmW generation because QD-CCLs with low power consumption and chip-scale integration capacity with silicon can provide multiple highly correlated and low noise optical channels. In this paper we will present our developed InAs/InP QD-CCLs around 1550 nm with the channel spacing from 10 GHz to 1000 GHz and the output power up to 50 mW. By using a C-band QD CCL and based on the single- and dual-optical carrier modulation schemes, an up to 16-Gb/s mmWoF optical heterodyne wireless signal at 28 GHz through a 25-km single mode fiber before the mmW carrier is optically synthesized remotely for detection over a 2-m free space. The data capacity and performance of the proposed mmWoF link can be significantly increased by utilizing a duplex mmWoF link with MIMO and WDM technique, which provides a cost-efficient and promising solution for Terabit/s capacity mmWoF fronthaul systems of B5G/6G networks. © 2024 SPIE.

关键词： Radio-over-fiber

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Joint alignment and steering to manage interference

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Digital Communications and Networks 2024年第2期10卷 429-438页

作者： Zhao Li Xiujuan Liang Yinghou Liu Jia Liu Zheng Yan School of Cyber Engineering Xidian UniversityXi'an710126China Technol.on Commun.Net.Lab. The 54th Research Inst.of China Elec.Technol.Group Corp.Shijiazhuang050081China School of Computer Science and Technology Xidian UniversityXi'an710126China The Department of Communications and Networking(Comnet) Aalto University02150EspooFinland

In wireless communication networks,mobile users in overlapping areas may experience severe interference,therefore,designing effective Interference Management(IM)methods is crucial to improving network ***,when managing multiple disturbances from the same source,it may not be feasible to use existing IM methods such as Interference Alignment(IA)and Interference Steering(IS)*** is because with IA,the aligned interference becomes indistinguishable at its desired Receiver(Rx)under the cost constraint of Degrees-of-Freedom(DoF),while with IS,more transmit power will be consumed in the direct and repeated application of IS to each *** remedy these deficiencies,Interference Alignment Steering(IAS)is proposed by incorporating IA and IS and exploiting their advantages in *** IAS,the interfering Transmitter(Tx)first aligns one interference incurred by the transmission of one data stream to a one-dimensional subspace orthogonal to the desired transmission at the interfered Rx,and then the remaining interferences are treated as a whole and steered to the same subspace as the aligned ***,two improved versions of IAS,i.e.,IAS with Full Adjustment at the Interfering Tx(IAS-FAIT)and Interference Steering and Alignment(ISA),are *** former considers the influence of IA on the interfering user-pair's *** orthogonality between the desired signals at the interfered Rx can be maintained by adjusting the spatial characteristics of all interferences and the aligned interference components,thus ensuring the Spectral Efficiency(SE)of the interfering communication *** ISA,the power cost for IS at the interfered Tx is minimized,hence improving SE performance of the interfered *** the proposed methods are realized at the interfering and interfered Txs cooperatively,the expenses of IM are shared by both *** in-depth simulation results show that joint use of IA and

关键词： Interference Interference management Interference alignment Interference steering Spectral efficiency

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Key Success Factor of Marketing Intelligence in Higher Education: Systematic Literature Review 8

Key Success Factor of Marketing Intelligence in Higher Educa...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Radhia, Fathy Christian, Albert Budi Putra, Edi Purnomo Hartono, Sugiarto Triantono, Henricus Bambang School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Coll. of Elec. Engineering and Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9798350326093

Marketing Intelligence (MI) is the process of collecting and applying information to formulate effective marketing strategies. Currently, the information on MI at XYZ University still does not fully describe the user's needs and it can be improved so that its use can be successfully used by end-users. The research question is what key success factors are needed to build marketing intelligence in higher education. The objective of this study is to ascertain the critical success factors of marketing intelligence needed by universities. This study uses a qualitative research method, namely SLR conducting a Systematic Literature Review (SLR) that involves a comprehensive analysis of marketing intelligence. This research produces several factors that determine the success of marketing intelligence, consisting of Technology;Strategic, Tactical, Operational;Small and Medium Enterprise (SM E)'s Performance;Predictors and Consequences;Customer Satisfaction and Loyalty;Environment;Concept, Overview;Sales Forces;External Intelligence;Internal Information;Talent Management;Individual Sources;Information Sources;Personal Factors;and Organizational. The impact of this research is that universities that aim to develop and implement marketing intelligence can pay attention to technology, personal factors, and strategic/tactical/operational variables which are the 3 critical variables for building marketing intelligence. © 2023 IEEE.

关键词： Customer satisfaction

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SCIM: Incorporating secure communication and interference management in one operation

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Digital Communications and Networks 2023年第2期9卷 512-522页

作者： Zhao Li Pintian Lyu Jun Li Zhixian Chang Jia Liu Zheng Yan School of Cyber Engineering Xidian UniversityXi'an710126China Technol.on Commun.Net.Lab The 54th Research Inst.of China Elec.Technol.Group CorpShijiazhuang050081China School of Telecommun.and Inf.Engineering Xi'an University of Posts&TelecommunXi'an710071China School of Computer Science and Technology Xidian UniversityXi'an710126China The Department of Comnet Aalto UniversityEspoo02150Finland

Due to the broadcast nature of wireless communications,users’data transmitted wirelessly is susceptible to security/privacy ***,as a result of the limitation of spectrum resources,massive wireless connections will incur serious interference,which may damage the efficiency of data ***,improving both efficiency and secrecy of data transmission is of research *** this paper,we propose a wireless transmission scheme by taking both Secure Communication(SC)and Interference Management(IM)into account,namely *** this scheme,an SCIM signal is generated by the legitimate transmitter(Tx)and sent along with the desired signal,so that the SCIM signal can interact with and suppress the environmental interference at the legitimate receiver(Rx).Meanwhile,the SCIM signal may interfere with the eavesdropper in the coverage of legitimate transmission so as to deteriorate the eavesdropping ***,the secrecy of desired transmission is *** this way,both the transmission efficiency and privacy are ***,by taking various transmission preferences into account,we develop different implementations of SCIM,including Interference Suppression First SCIM(ISF-SCIM),Data Transmission First SCIM(DTF-SCIM),Anti-Eavesdropping First SCIM(AEF-SCIM),and Secrecy Rate Maximization SCIM(SRM-SCIM).Our in-depth simulation results have shown the proposed methods to effectively improve the efficiency and secrecy of the legitimate transmission.

关键词： Physical-layer security Secure communication Anti-eavesdropping Interference management Secrecy rate

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Initial Impact of Evidence-Based and Experiment-Focused Teaching Approach in a computer Architecture Course in computer science

Initial Impact of Evidence-Based and Experiment-Focused Teac...

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2022 International Conference on Computational science and Computational Intelligence, CSCI 2022

作者： Rahman, Md Mahmudur Adeniran, Opeyemi Shourabi, Neda Bazyar Owolabi, Oludare Morgan State University Computer Science Department BaltimoreMD United States Morgan State University Department of Elec. Engineering BaltimoreMD United States Morgan State University Department of Civil Engineering BaltimoreMD United States

ISBN: (纸本)9798350320282

The Digital Logic and computer Architecture related courses are one of the key knowledge areas in computer science (CS) used to enhance students' understanding of Boolean algebra, logic gates, registers, arithmetic logic units, etc. and provides insights how software and hardware are related in a computing system. Experimental Centric based Instructional Pedagogy (ECP) with portable laboratory instrumentation might provide real hands-on experience to obtain a practical understanding of the concepts at a lower cost compared to virtual hands-on laboratories. This paper presents the initial adaptation of an evidence-based, experiment-focused teaching approach to introduce the fundamentals of digital logic concepts using the commercial ADALM 1K Active Learning Module in a computer Architecture course for the first time in the CS department at a university serving predominantly minority students. To evaluate the impact of the ECP on student performance in the computer Architecture course, we conducted three different evaluations, which are class observation, signature assignment, and the Motivated Strategies for Learning Questionnaires (MLSQ) survey. The results of the Classroom Observation Protocol for Undergraduate STEM (COPUS) show more student engagement when ECP is implemented;the output of the signature assignment shows an increase in students' learning outcomes;and the MLSQ survey, which tests the students' motivation, critical thinking, curiosity, collaboration, and metacognition, ascertains the effect of the ECP on the CS students who participated in the experiment. © 2022 IEEE.

关键词： Students

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Boosting the Prediction of Brain Tumor Using Two Stage BiGait Architecture

Boosting the Prediction of Brain Tumor Using Two Stage BiGai...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Saif-ur-Rehman Khan Zia Khan Md Zakir Hossain Nicanor Mayumu Farhana Yasmin Younas Aziz School of Computer Science and Engineering Central South University Changsha China School of Elec Eng Comp and Math Sci (EECMS) Curtin University Perth Australia Department of Computer and Software Nanjing University of information Science and Technology Nanjing

ISBN: (数字)9798350379037

ISBN: (纸本)9798350379044

Deep learning (DL) techniques hold immense promise for revolutionizing medical diagnostics, including brain tumor detection. Detecting malignancies in the brain is fraught with challenges that carry critical implications for accurate and timely diagnosis. Early detection is paramount, and our paper presents a novel approach to address this issue. We introduce the BiGait ensemble transfer learning (TL) architecture tailored for brain tumor classification tasks. Our proposed methodology is a two-stage process that harnesses the power of TL. In the initial phase, we employ two established models, ResNet50 and EfficientNetB1, and fine-tune them using the Kaggle multiclass dataset. This includes the incorporation of supplementary feature layers. We also leverage a stack ensemble solution to combine these feature layers, enhancing the model's overall predictive capabilities. Our approach is designed to shift the input distribution positively, effectively mitigating overfitting and reducing hardware overhead. To validate the effectiveness of our method, we conducted extensive experiments and evaluation. The dataset utilized in this work, publicly available on Kaggle contains 3,264 brain MRIs categorized into four groups: normal (500 images), meningioma (937 images), glioma (926 images), and pituitary tumor (901 images). The experimental results demonstrate that our model surpasses traditional single-model approaches, achieving an impressive accuracy rate of 96% and exhibiting superior generalization capabilities. This advancement in brain tumor classification holds great promise for early diagnosis and improved patient outcomes.

关键词： Accuracy Transfer learning Brain tumors computer architecture Predictive models Brain modeling Reliability Medical diagnosis Residual neural networks Overfitting

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HRPE-Enhanced AI-Based 5G Indoor Localization in Presence of Specular and Dense Multipaths

HRPE-Enhanced AI-Based 5G Indoor Localization in Presence of...

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European Conference on Antennas and Propagation, EuCAP

作者： Yuchen Shi Xiaoxiao Yang Yuying Sun José Rodríguez-Piñeiro Xueming Hong Tomás Domínguez-Bolaño Xuefeng Yin College of Electronics and Information Engineering Tongji University Shanghai China School of Elec. Science and Engineering Xiamen University China School of Informatics Xiamen University China CITIC Research Center & Department of Computer Engineering University of A Coruña Spain

Fifth generation (5G) communication systems are expected to provide an ubiquitous solution for indoor positioning, and deep neural networks (DNNs) have been recently proposed for this purpose. However, DNN-based positioning solutions are in general very dependent on the training data. In this paper, an architecture for positioning based on wireless signals is proposed, namely the SAGE-Enhanced CEAP (SE-CEAP). The architecture considers firstly an enhancement of the acquired Channel State Information (CSI) data by means of a high-resolution parameter estimation (HRPE) method, namely the space-alternating generalized-expectation maximization (SAGE) algorithm, and secondly a specifically designed DNN for localization, namely the CNN-Enblock AI Positioning (CEAP). The provided results, considering a realistic 5G New Radio (NR) deployment in an indoor scenario, show that the proposed architecture outperforms other classical DNN-based localization approaches, not only in localization accuracy, but also in generalizability of the results, which is a common drawback of DNN-based solutions.

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Grid Impedance Adaptive VSG Control Based on Accurate Small-Signal Modelling

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IEEE Transactions on Industry Applications 2025年

作者： Wang, Minyang Yang, Yuxin Zhang, Yuchen Ambia, Mir Nahidual Ahmed, Al-Durra Zhang, Daming Meng, Ke Zhang, Ge University of New South Wales School of Elec Eng and Telco Faculty of Engineering NSW Australia Queensland University of Technology School of Electrical Engineering and Robotics Brisbane Australia University of Sydney Sydney Australia Principal Grid Connection Engineer at Nordex Oceania Australia Khalifa University Electrical Engineering and Computer Science Department Abu Dhabi United Arab Emirates ElectraNet Pty Ltd Adelaide Australia University of Queensland School of Electrical Engineering and Computer Science Brisbane Australia

The wide-spread integration of renewable energy has increased inverter-based generation, weakening grid strength and inertia, bringing challenges to power system stability. To address these issues, virtual synchronous generator (VSG) control has emerged as a modern grid-forming (GFM) technology that can autonomously provide active and reactive power to support grid frequency and voltage. However, when a VSG inverter operates under strong grid conditions, power oscillations may occur under a fixed parameter setting, making the grid difficult to reach a steady state. Under such circumstances, traditional stability analysis based on the rate of change of frequency (RoCoF) is insufficient, advanced analysis methods based on the changes in system impedance and further improvements are required. This paper proposed an accurate small-signal model of the VSG inverter along with an impedance identification method for grid impedance. Additionally, an improved VSG control adaptive to grid impedance is proposed based on the knowledge of small-signal model and system impedance. All proposed methods have been tested on a single-machine-infinite-bus (SMIB) system and the stability results demonstrate their effectiveness under both weak and strong grid scenarios. © 1972-2012 IEEE.

关键词： Synchronous generators

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Domain Adaptation for Classifying Spontaneous Smile Videos

Domain Adaptation for Classifying Spontaneous Smile Videos

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Amrijit Biswas Md Zakir Hossain Yan Yang Syed Mohammed Shamsul Islam Tom Gedeon Shafin Rahman Department of Electrical and Computer Engineering (ECE) North South University Bangladesh School of Computing Australian National University Canberra Australia School of Elec Eng Comp and Math Sci (EECMS) Curtin University Perth Australia School of Science Edith Cowan University Perth Australia

ISBN: (数字)9798350379037

ISBN: (纸本)9798350379044

Distinguishing spontaneous and posed smiles has become an exciting topic due to its potential application in several sectors. However, it is a very challenging task, even for humans. Past researchers have proposed several semi and fully automatic approaches for smile classification. These approaches have explored both feature-based engineering and end-to-end deep neural network-based strategies. One major issue with past methods is the degradation of performance when deploying the model in a data domain different from the training domain, as smile patterns are different across diverse groups (e.g., young, adult, male, and female). In this paper, we present an end-to-end domain adaptation model to address these problems. We explore a new unsupervised domain adaptation application for smile veracity recognition. We propose an identity-invariant learning objective to align the training (source) data knowledge to the testing (target) data. Our approach penalizes identity information hidden in the feature space by enhancing sufficient distinctiveness among different smile phase features while maintaining inter-class cohesion. We have used UVA-NEMO, MMI, SPOS, and BBC datasets to validate the performance of our model and found that our domain adaptation approach outperforms the existing models by achieving state-of-the-art performance.

关键词： Training Degradation Adaptation models Computational modeling Digital images Manuals Interference Data models Testing Videos

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