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19th European Conference on Antennas and Propagation, EuCAP 2025

作者： Thakkar, Shrey Ruiz-García, Jorge Szymanski, Luke Gok, Gurkan Grbic, Anthony University of Michigan Department of Electrical Engineering and Computer Science Ann Arbor United States Mit Lincoln Laboratory Lexington United States Raytheon Technologies Research Center East Hartford United States

ISBN: (纸本)9788831299107

This work reports an inverse design method for perfectly-matched metamaterials (PMMs) with multi-input multi-output (MIMO) functionality. PMMs are inhomogeneous, anisotropic 2-D metamaterials composed of unit cells that remain impedance-matched to each other and the surrounding medium. These reflectionless devices rely on refractive effects to perform field transformations, exhibiting true time delay behavior and broadband operation. The paper improves on a previously reported inverse design method on two fronts. First, the objective function is modified to match desired voltage magnitudes and phase profiles. Importantly, the objective function allows phase profiles to have an arbitrary phase offset instead of absolute phase values. Second, an absorbing boundary condition is imposed on all boundaries of the computational domain. As an example, a compact and broadband beamformer is presented. The device transforms the field of a line source to the far-field radiation pattern of a Dolph-Chebyshev array of the same size with a -20 dB sidelobe level. © 2025 European Association on Antennas and Propagation.

关键词： Beamforming broadband inverse design metamaterials multiple input multiple output optimization

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Federated Learning Based Integrated Sensing, Communications, and Powering Over 6G Massive-MIMO Mobile Networks

Federated Learning Based Integrated Sensing, Communications,...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9798350384475

ISBN: (纸本)9798350384482

To sense mobile users' positions and channel states while simultaneously conveying information for supporting the 6G traffic, the integrated sensing and communication (ISAC) has been proposed as a key technique for sensing and communicating using the same radio frequency and hardware. Moreover, to sup-port energy-constrained and battery-limited wireless networks, simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. To integrate these two techniques, integrated sensing, communications, and powering (ISACP) has been developed to simultaneously sense the targeted mobile users, transmit the information, and deliver the power. However, how to efficiently optimize the power allocation in ISACP schemes to support the 6G traffic has imposed many new challenges not encountered before. To overcome these challenges, in this paper we propose a federated-learning (FL) enabled ISACP scheme to maximize the energy-efficiency over 6G massive MIMO wireless networks. First, we establish the system models for our proposed ISACP and FL schemes. Second, we design the training data set collection in the FL algorithm by sending the pilot signal from mobile users to the massive MIMO base station, and formulate an energy-efficiency maximization problem for the developed ISACP scheme. Third, To solve the formulated energy-efficiency maxi-mization problem, we propose an actorcritic enabled multi-agent based FL mechanism. Finally, we use the numerical analyses to validate and evaluate our developed schemes.

关键词： 6G mobile communication Wireless sensor networks Federated learning Wireless networks Training data Massive MIMO Integrated sensing and communication

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ISAC-Driven Channel-State-Estimation for Statistical-QoS Based MURLLC Over 6G M-MIMO Mobile Networks Using FBC

ISAC-Driven Channel-State-Estimation for Statistical-QoS Bas...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Xi Zhang Qixuan Zhu Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas A&M University College Station TX USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support communications among massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements in 6G. Correspondingly, the integrated sensing and communications (ISAC) technique can improve various QoS performances through spectrum/hardware sharing between target-sensing and data-communications. In addition, the massive multiple-input multiple-output (massive MIMO) and finite blocklength coding (FBC) have been also widely recognized as the powerful 6G techniques to efficiently support mURLLC. However, how to apply the ISAC technique to accurately sense and estimate the wireless channel state while transmitting the information from the base station to MUs to support mURLLC using massive MIMO and FBC has imposed many new difficulties not encountered before. To conquer these challenges, in this paper we propose the new ISAC performance metrics for statistical-QoS guaranteed mURLLC over 6G massive MIMO mobile networks using FBC. First, we establish system models for ISAC-based architectures. Second, we detect targeted MUs and estimate the channel state using the radar sensing echo. Third, we develop a new ISAC performance metric as a function of the data-communication rate and channel state estimation distortion. Finally, we use the numerical analyses to validate and evaluate our developed ISAC performances in supporting mURLLC-oriented QoS requirements.

关键词： 6G mobile communication Measurement Wireless sensor networks Wireless networks Channel estimation Quality of service Massive MIMO Integrated sensing and communication Distortion Testing

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OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning

arXiv

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arXiv 2024年

作者： Yue, Sheng Hua, Xingyuan Ren, Ju Lin, Sen Zhang, Junshan Zhang, Yaoxue Department of Computer Science and Technology Tsinghua University Beijing China Zhongguancun Laboratory Beijing China Department of Computer Science University of Houston TX United States Department of Electrical and Computer Engineering University of California Davis United States

In this paper, we study offline-to-online Imitation Learning (IL) that pretrains an imitation policy from static demonstration data, followed by fast finetuning with minimal environmental interaction. We find the naïve combination of existing offline IL and online IL methods tends to behave poorly in this context, because the initial discriminator (often used in online IL) operates randomly and discordantly against the policy initialization, leading to misguided policy optimization and unlearning of pretraining knowledge. To overcome this challenge, we propose a principled offline-to-online IL method, named OLLIE, that simultaneously learns a near-expert policy initialization along with an aligned discriminator initialization, which can be seamlessly integrated into online IL, achieving smooth and fast finetuning. Empirically, OLLIE consistently and significantly outperforms the baseline methods in 20 challenging tasks, from continuous control to vision-based domains, in terms of performance, demonstration efficiency, and convergence speed. This work may serve as a foundation for further exploration of pretraining and finetuning in the context of IL. Copyright © 2024, The Authors. All rights reserved.

关键词： E-learning

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Modelling the Effect of the DC Link Decoupling Capacitor of a Commutation Power Loop Using a Thevenin-Based Frequency Domain Approach

Modelling the Effect of the DC Link Decoupling Capacitor of ...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Ayooluwa Ajiboye Ayodhya Somiruwan Gamwari Rakesh Resalayyan Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory The Institute for Systems Research University of Maryland College Park USA

The high commutation speed of wide band-gap devices causes undesired voltage overshoots and oscillatory behavior observed across the drain-source port. The mitigation of these voltage overshoots and oscillations caused by the resonant interaction between the commutation loop parasitic inductance and the switch parasitic output capacitance requires additional design considerations. In this work, a Thevenin-based frequency domain approach for modelling the switch voltage overshoot and oscillations with respect to the commutation power loop is proposed. The switching transition and its associated slew rate is modelled using a clamped-ramp function. The two figures of merit used to quantify the effect of the circuit elements in the commutation power loop with respect to the resonant oscillations are the voltage overshoot and time to steady state. Using the clamped-ramp function and the two figures of merit, the effect of the parasitic inductance and the decoupling capacitor on the power loop is analyzed. The trends observed from the analyses are used to obtain recommendations regarding the sizing and placement of the decoupling capacitor in the power loop. The proposed Thevenin-based frequency domain model is experimentally validated by comparing the analytical results with both the LTspice simulations and the experimental waveforms for a SiC-based 400 V, 20 A double pulse test.

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Abstract: A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT

Abstract: A Spatiotemporal Model for Precise and Efficient F...

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Bildverarbeitung für die Medizin Workshop, BVM 2023

作者： Ploner, Stefan B. Chen, Siyu Won, Jungeun Husvogt, Lennart Breininger, Katharina Schottenhamml, Julia Fujimoto, James G. Maier, Andreas K. Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Germany Department of Electrical Engineering and Computer Science Research Laboratory for Electronics Massachusetts Institute of Technology CambridgeMA United States

ISBN: (纸本)9783658416560

Optical coherence tomography (OCT) is a micrometer-scale, volumetric imaging modality that has become a clinical standard in ophthalmology. OCT instruments image by raster-scanning a focused light spot across the retina, acquiring sequential cross-sectional images to generate volumetric data. Patient eye motion during the acquisition poses unique challenges: Non-rigid, discontinuous distortions can occur, leading to gaps in data and distorted topographic measurements. We present a new distortion model and a corresponding fully-automatic, reference-free optimization strategy for computational motion correction in orthogonally raster-scanned, retinal OCT volumes. Using a novel, domain-specific spatiotemporal parametrization of forward-warping displacements, eye motion can be corrected continuously for the first time. Parameter estimation with temporal regularization improves robustness and accuracy over previous spatial approaches. We correct each A-scan individually in 3D in a single mapping, including repeated acquisitions used in OCT angiography protocols. Specialized 3D forward image warping reduces median runtime to © 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.

关键词： Optical tomography

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Attentive Hawkes Process Application for Sequential Recommendation 28th

Attentive Hawkes Process Application for Sequential Recomme...

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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Yu, Shuodian Ma, Li Gao, Xiaofeng Guo, Jianxiong Chen, Guihai Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China

ISBN: (纸本)9783031306716

Sequential recommendation systems which aim to predict the users’ future clicking items are essential in both research and industry services. Based on the contextual characteristics of users, a large number of existing methods exploit abundant information from user behavior sequences and gain users’ interests through expressive sequential models like recurrent neural networks and self-attention mechanism to predict the next item. However, the temporal generative process of behavior sequences, which is crucial to the complex relationships and distributions of users’ dynamic preferences, is rarely considered. In this paper, we propose HawRec (Hawkes process based sequential recommendation), which is a new representation learning approach to model the interacted sequences of users from a temporal point process perspective. In particular, we leverage temporal self-attention mechanism to make an analogy to the self-exciting mechanism of Hawkes process. We bring expressive superiority of neural network into the Hawkes process with non-parametric conditional intensity kernel, resulting in more accurate recommendation and inheriting robustness from the temporal point process. Furthermore, extensive experiments conducted on four public benchmarks demonstrate that our HawRec outperforms various baselines of state-of-the-art sequential recommendation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach

arXiv

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arXiv 2025年

作者： Liu, Yuhan Kiss, Máté Tóth, Roland Schoukens, Maarten Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest1111 Hungary

While optimal input design for linear systems has been well-established, no systematic approach exists for nonlinear systems, where robustness to extrapolation/interpolation errors is prioritized over minimizing estimated parameter variance. To address this issue, we develop a novel identification-oriented space-filling input design strategy for efficient covering of a well-defined region of interest. By placing a Gaussian Process (GP) prior on the joint input-state space, the proposed strategy leverages the GP posterior variance to construct a space-filling promoting input design cost function from the Bayesian point of view. This accordingly enables maximization of the coverage in the region of interest, thereby facilitating the generation of informative datasets. Furthermore, we theoretically prove that minimization of the cost function indicates the space-filling behavior. The effectiveness of the proposed strategy is demonstrated on both an academic example and a mass-spring-damper system, highlighting its potential practical impact on efficient exploration in identification scenarios for nonlinear dynamical systems. © 2025, CC BY-NC-SA.

关键词： Cost functions

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Efficient fully analytical polygon-based continuous shading rendering CGH algorithm with specular reflection 14

Efficient fully analytical polygon-based continuous shading ...

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Holography, Diffractive Optics, and Applications XIV 2024

作者： Wang, Pin Fu, Qingyang Zhang, Yaping Poon, Ting-Chung Yunnan Provincial Key Laboratory of Modern Information Optics Kunming University of Science and Technology Kunming Yunnan650500 China Nanjing University of Science and Technology Nanjing Jiangsu210094 China Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

ISBN: (纸本)9781510682085

The fully analytical method has been widely studied for its higher accuracy and efficiency, and the addition of shading rendering can effectively improve the three-dimensional perception of reconstructed images. However, existing fully analytical polygon-based shading rendering methods suffer from high computational complexity and complexity due to the need for additional calculation of the highlight spectrum. Based on previous research, we employ a continuous light and shadow algorithm that uses linear interpolation to decouple the reflection term from the spectrum, meaning that we incorporate the specular component into the calculation of vertex modulus, and separately compute the vertex modulus and the corresponding spectrum values, simplifying the calculation process of existing Blinn Phong lighting models. The algorithm can effectively generate highly realistic holographically reconstructed images with high gloss effects under continuous illumination. It achieves computational efficiency than existing algorithms, without increasing the number of polygons. Simulations and experimental results have verified the effectiveness of our proposed method. © 2024 SPIE. All rights reserved.

关键词： Rendering (computer graphics)

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Integrated Sensing, Communications, and Powering for Statistical-QoS Provisioning Over 6G Massive-MIMO Mobile Networks Using FBC

Integrated Sensing, Communications, and Powering for Statist...

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IEEE International Conference on Communications (ICC)

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

To satisfy the stringent quality-of-service (QoS) requirements of 6G mobile wireless networks on both channel state estimations and information transmissions, the integrated sensing and communication (ISAC) has been an enabling technique to sense and communicate by sharing the same frequency band and hardware. Simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. However, how to integrate ISAC with SWIPT to support the 6G traffic has imposed many new challenges not encountered before. To conquer these difficulties, in this paper we propose an integrated sensing, communications, and powering (ISACP) scheme for supporting statistical-QoS provisioning over 6G wireless networks using massive multiple-input and multiple-output (massive MIMO) communications. First, we establish system models for our ISACP scheme and define the Cramér-Rao bound and channel estimation distortion under our proposed ISACP scheme. Second, we develop the performance metrics of Cramér-Rao bound and channel estimation distortion to derive the capacity-distortion function to jointly measure the performance of integrated sensing, communication, and powering. Third, we integrate the capacity-distortion function with the finite blocklength coding (FBC) through deriving the ISACP-based ϵ-effective capacity to support the statistical delay and error-rate bounded QoS provisioning in 6G. Fourth, we maximize the energy-efficiency by controlling the optimal wireless power transfer for our ISACP scheme. Finally, we use numerical analyses to validate and evaluate our proposed ISACP scheme.

关键词： 6G mobile communication Wireless sensor networks Wireless networks Channel estimation Quality of service Integrated sensing and communication Distortion

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