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arXiv 2024年

作者： Xiu, Yue Zhao, Yang Yang, Ran Tang, Huimin Qu, Long Khabbaz, Maurice Assi, Chadi Wei, Ning National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China Nanyang Technological University 50 Nanyang Ave Singapore639798 Singapore Cho Chun Shik Graduate School of Mobility Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China CMPS Department American University of Beirut Lebanon Concordia University MontrealQCH3G 1M8 Canada

Device-to-device (D2D)-assisted mobile edge computing (MEC) is one of the critical technologies of future sixth generation (6G) networks. The core of D2D-assisted MEC is to reduce system latency for network edge UEs by supporting cloud computing services, thereby achieving high-speed transmission. Due to the sensitivity of communication signals to obstacles, relaying is adopted to enhance the D2D-assisted MEC system’s performance and its coverage area. However, relay nodes and the base station (BS) are typically equipped with large-scale antenna arrays. This increases the cost of relay-assisted D2D MEC systems and limits their deployment. Movable antenna (MA) technology is used to work around this limitation without compromising performance. Specifically, the core of MA technology lies in optimizing the antenna positions to increase system capacity. Therefore, this paper proposes a novel resource allocation scheme for MA-enhanced relay-assisted D2D MEC systems. Specifically, the MA positions and beamforming of user equipments (UEs), relay, and BS as well as the allocation of resources and the computation task offloading rate at the MEC server, all are optimized herein with the objective of minimizing the maximum latency while satisfying computation and communication rate constraints. Since this is a multivariable non-convex problem, a parallel and distributed penalty dual decomposition (PDD) based algorithm is developed and combined with successive convex approximation (SCA) to solve this nonconvex problem. The results of extensive numerical analyses show that the proposed algorithm significantly improves the performance of the MA-enhanced relay-assisted D2D communication system compared to a counterpart where relays and the BS are equiped with traditional fixed-position antenna (FPA). Copyright © 2024, The Authors. All rights reserved.

关键词： Computation offloading

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Mind the Õ: asymptotically better, but still impractical, quantum distributed algorithms

arXiv

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arXiv 2023年

作者： Kerger, Phillip A. Bernal Neira, David E. Izquierdo, Zoe Gonzalez Rieffel, Eleanor G. Department of Applied Mathematics and Statistics Johns Hopkins University United States Research Institute of Advanced Computer Science USRA United States Quantum Artificial Intelligence Laboratory NASA Ames Research Center United States Davidson School of Chemical Engineering Purdue University United States

The CONGEST and CONGEST-CLIQUE models have been carefully studied to represent situations where the communication bandwidth between processors in a network is severely limited. Messages of only O(log(n)) bits of information each may be sent between processors in each round. The quantum versions of these models allow the processors instead to communicate and compute with quantum bits under the same bandwidth limitations. This leads to the following natural research question: What problems can be solved more efficiently in these quantum models than in the classical ones? Building on existing work, we contribute to this question in two ways. Firstly, we present two algorithms in the Quantum CONGEST-CLIQUE model of distributed computation that succeed with high probability;one for producing an approximately optimal Steiner Tree, and one for producing an exact directed minimum spanning tree, each of which uses Õ(n1/4) rounds of communication and Õ(n9/4) messages, where n is the number of nodes in the network. The algorithms thus achieve a lower asymptotic round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. At a high level, we achieve these results by combining classical algorithmic frameworks with quantum subroutines. An existing framework for using a distributed version of Grover’s search algorithm to accelerate triangle finding lies at the core of the asymptotic speedup. Secondly, we carefully characterize the constants and logarithmic factors involved in our algorithms as well as related algorithms, otherwise commonly obscured by Õ notation. The analysis shows that some improvements are needed to render both our and existing related quantum and classical algorithms practical, as their asymptotic speedups only help for very large values of n. © 2023, CC BY.

关键词： Bandwidth

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Ga2O3 Heterojunction PN Diodes with Suppressed Background Carrier Concentration for Improved Breakdown Voltage

Ga2O3 Heterojunction PN Diodes with Suppressed Background Ca...

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Device Research Conference

作者： Pengfei Dong Chenlu Wang Qinglong Yan Yingming Wang Jian Wang Sami Alghamdi Zhihong Liu Jincheng Zhang Hong Zhou Yue Hao State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology School of Microelectronics Xidian University Xi'an China Key Laboratory of Advanced Semiconductor Materials of CETC The 46th Research Institute China Electronics Technology Group Corporation Tianjin 300220 China Electrical and Computer Engineering department King Abdulaziz University Jeddah Saudi Arabia

In this paper, we show that by suppressing the background carrier concentration, the breakdown voltage (BV) of Ga 2 O 3 heterojunction PN diode (HJ-PND) can be essentially enhanced. Meanwhile, through combing with high-level hole injection induced conductivity modulation effect, the specific on-resistance (R on, sp ) can be significantly reduced. Even without a carefully designed edge termination, a high power figure of merit (P- $\text{FOM}=\text{BV}^{2}/\mathrm{R}_{\text{on},\text{sp}})$ of $(3.75\ \text{kV})^{2}/(2.5\ \mathrm{m}\Omega\cdot \text{cm}^{2})=5.6\ \text{GW}/\text{cm}^{2}$ can be achieved. Ga 2 O 3 HJ PN diodes with suppressed background carrier concentration for BV enhancement and high-level hole injection for Ron, sp reduction verify their great promise for future high voltage and high power applications.

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Nano device fabrication for in-memory and in-sensor reservoir computing

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International Journal of Extreme Manufacturing 2025年第1期7卷 46-71页

作者： Yinan Lin Xi Chen Qianyu Zhang Junqi You Renjing Xu Zhongrui Wang Linfeng Sun Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement(MOE)School of PhysicsBeijing Institute of TechnologyBeijing 100081People’s Republic of China Beijing Key Laboratory of Nanophotonics&Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of TechnologyBeijing 100081People’s Republic of China Department of Electrical and Electronic Engineering The University of Hong KongPokfulam RoadHong Kong Special Administrative Region of ChinaPeople’s Republic of China ACCESS-AI Chip Center for Emerging Smart Systems InnoHK CentersHong Kong Science ParkHong Kong Special Administrative Region of ChinaPeople’s Republic of China School of Microelectronics Southern University of Science and TechnologyShenzhen 518055People’s Republic of China Thrust of Microelectronics of Function Hub The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511400People’s Republic of China

Recurrent neural networks(RNNs)have proven to be indispensable for processing sequential and temporal data,with extensive applications in language modeling,text generation,machine translation,and time-series *** their versatility,RNNs are frequently beset by significant training expenses and slow convergence times,which impinge upon their deployment in edge AI *** computing(RC),a specialized RNN variant,is attracting increased attention as a cost-effective alternative for processing temporal and sequential data at the ***’s distinctive advantage stems from its compatibility with emerging memristive hardware,which leverages the energy efficiency and reduced footprint of analog in-memory and in-sensor computing,offering a streamlined and energy-efficient *** review offers a comprehensive explanation of RC’s underlying principles,fabrication processes,and surveys recent progress in nano-memristive device based RC systems from the viewpoints of in-memory and in-sensor RC *** covers a spectrum of memristive device,from established oxide-based memristive device to cutting-edge material science developments,providing readers with a lucid understanding of RC’s hardware implementation and fostering innovative designs for in-sensor RC ***,we identify prevailing challenges and suggest viable solutions,paving the way for future advancements in in-sensor RC technology.

关键词： reservoir computing memristive device fabrication compute-in-memory in-sensor computing

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A Study on the Efficient Design of Adders Using Adiabatic Quantum-Flux-Parametron Circuits

A Study on the Efficient Design of Adders Using Adiabatic Qu...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Tomoharu Yamauchi Hao San Nobuyuki Yoshikawa Olivia Chen Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Department of Electrical Electronics and Communication Engineering Tokyo City University Tokyo Japan Institute of Advanced Sciences Yokohama National University Kanagawa Japan Department of Computer Science Tokyo City University Tokyo Japan

ISBN: (纸本)9781665492331

Adiabatic quantum-flux-parametron (AQFP) logic is a promising technology for future energy-efficient, high-performance information processing systems. It has significantly low power consumption thanks to the adiabatic switching of Josephson junctions. In this paper, we proposed an AQFP-based Kogge-Stone adder (KSA) to achieve low energy consumption. Moreover, we proposed an offset buffer based XOR macro to improve the hardware overhead. The proposed work achieves a 21% and 6% reduction in total Josephson junction count and circuit area, respectively.

关键词： Energy consumption Power demand Design methodology Switches Information processing Josephson junctions Hardware

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On the Study of Success Serving Probability for Integrated Sensing and Communication (ISAC) Based on Stochastic Geometry

On the Study of Success Serving Probability for Integrated S...

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IEEE International Conference on Communications (ICC)

作者： Wentao Cheng Zhongyuan Zhao Howard H. Yang Wei Hong Tony Q.S. Quek Zhiguo Ding The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China ZJU-UIUC Institute Zhejiang University Haining China Beijing Xiaomi Mobile Software Beijing China Singapore University of Technology and Design Singapore Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Integrated sensing and communication (ISAC) has been proved as a promising technique to further improve the performance for both the communication and the sensing tasks in wireless networks. However, due to the complicated and dynamic interference circumstances, the performance of ISAC cannot be guaranteed. To provide some insights for keeping a sophisticated balance between communication and sensing with considering co-channel interference, the theoretical performance of ISAC is studied in this paper. First, an analytical system model is provided based on stochastic geometry. Second, the success serving probability (SSP) is defined for both the communication and the sensing tasks based on mutual information, which provided a unified analysis framework for ISAC. The tractable expressions of SSP are also derived. Finally, the simulation results are shown to verify the analytical results of SSP, which can provide some insights for the tradeoff between sensing and communication of ISAC.

关键词： Geometry Measurement Monte Carlo methods Wireless networks Simulation Stochastic processes Integrated sensing and communication

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μ-STAR: A novel framework for spatio-temporal M/EEG source imaging optimized by microstates

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NeuroImage 2023年 282卷 120372-120372页

作者： Feng, Zhao Wang, Sujie Qian, Linze Xu, Mengru Wu, Kuijun Kakkos, Ioannis Guan, Cuntai Sun, Yu Key Laboratory for Biomedical Engineering of Ministry of Education of China Department of Biomedical Engineering Zhejiang University Hangzhou China Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Greece School of Computer Science and Engineering Nanyang Technological University Singapore Ministry of Education Frontiers Science Center for Brain Science and Brain-Machine Integration Zhejiang University Hangzhou China State Key Laboratory for Brain-Machine Intelligence Zhejiang University Hangzhou China Department of Neurology Sir Run Run Shaw Hospital Zhejiang University School of Medicine Hangzhou China

Source imaging of Electroencephalography (EEG) and Magnetoencephalography (MEG) provides a noninvasive way of monitoring brain activities with high spatial and temporal resolution. In order to address this highly ill-posed problem, conventional source imaging models adopted spatio-temporal constraints that assume spatial stability of the source activities, neglecting the transient characteristics of M/EEG. In this work, a novel source imaging method μ-STAR that includes a microstate analysis and a spatio-temporal Bayesian model was introduced to address this problem. Specifically, the microstate analysis was applied to achieve automatic determination of time window length with quasi-stable source activity pattern for optimal reconstruction of source dynamics. Then a user-specific spatial prior and data-driven temporal basis functions were utilized to characterize the spatio-temporal information of sources within each state. The solution of the source reconstruction was obtained through a computationally efficient algorithm based upon variational Bayesian and convex analysis. The performance of the μ-STAR was first assessed through numerical simulations, where we found that the determination and inclusion of optimal temporal length in the spatio-temporal prior significantly improved the performance of source reconstruction. More importantly, the μ-STAR model achieved robust performance under various settings (i.e., source numbers/areas, SNR levels, and source depth) with fast convergence speed compared with five widely-used benchmark models (including wMNE, STV, SBL, BESTIES, & SI-STBF). Additional validations on real data were then performed on two publicly-available datasets (including block-design face-processing ERP and continuous resting-state EEG). The reconstructed source activities exhibited spatial and temporal neurophysiologically plausible results consistent with previously-revealed neural substrates, thereby further proving the feasibility of the μ-STAR m

关键词： Bayesian framework Microstates Source imaging Temporal segmentation

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Electromagnetic Channel Modeling and Capacity Analysis for HMIMO Communications

arXiv

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arXiv 2025年

作者： Wei, Li Yuan, Shuai S.A. Huang, Chongwen Zhang, Jianhua Bader, Faouzi Zhang, Zhaoyang Muhaidat, Sami Debbah, Mérouane Yuen, Chau School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates KU 6G Research Center Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada KU 6G Research Center Khalifa University of Science and Technology P O Box 127788 Abu Dhabi United Arab Emirates

Advancements in emerging technologies, e.g., reconfigurable intelligent surfaces and holographic MIMO (HMIMO), facilitate unprecedented manipulation of electromagnetic (EM) waves, significantly enhancing the performance of wireless communication systems. To accurately characterize the achievable performance limits of these systems, it is crucial to develop a universal EM-compliant channel model. This paper addresses this necessity by proposing a comprehensive EM channel model tailored for realistic multi-path environments, accounting for the combined effects of antenna array configurations and propagation conditions in HMIMO communications. Both polarization phenomena and spatial correlation are incorporated into this probabilistic channel model. Additionally, physical constraints of antenna configurations, such as mutual coupling effects and energy consumption, are integrated into the channel modeling framework. Simulation results validate the effectiveness of the proposed probabilistic channel model, indicating that traditional Rician and Rayleigh fading models cannot accurately depict the channel characteristics and underestimate the channel capacity. More importantly, the proposed channel model outperforms free-space Green’s functions in accurately depicting both near-field gain and multi-path effects in radiative near-field regions. These gains are much more evident in tri-polarized systems, highlighting the necessity of polarization interference elimination techniques. Moreover, the theoretical analysis accurately verifies that capacity decreases with expanding communication regions of two-user communications. Copyright © 2025, The Authors. All rights reserved.

关键词： Antenna arrays

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Touchstone benchmark: are we on the right way for evaluating AI algorithms for medical segmentation? 24

Touchstone benchmark: are we on the right way for evaluating...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Pedro R. A. S. Bassi Wenxuan Li Yucheng Tang Fabian Isensee Zifu Wang Jieneng Chen Yu-Cheng Chou Saikat Roy Yannick Kirchhoff Maximilian Rokuss Ziyan Huang Jin Ye Junjun He Tassilo Wald Constantin Ulrich Michael Baumgartner Klaus H. Maier-Hein Paul Jaeger Yiwen Ye Yutong Xie Jianpeng Zhang Ziyang Chen Yong Xia Zhaohu Xing Lei Zhu Yousef Sadegheih Afshin Bozorgpour Pratibha Kumari Reza Azad Dorit Merhof Pengcheng Shi Ting Ma Yuxin Du Fan Bai Tiejun Huang Bo Zhao Haonan Wang Xiaomeng Li Hanxue Gu Haoyu Dong Jichen Yang Maciej A. Mazurowski Saumya Gupta Linshan Wu Jiaxin Zhuang Hao Chen Holger Roth Daguang Xu Matthew B. Blaschko Sergio Decherchi Andrea Cavalli Alan L. Yuille Zongwei Zhou Department of Computer Science Johns Hopkins University and Department of Pharmacy and Biotechnology University of Bologna and Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Department of Computer Science Johns Hopkins University NVIDIA Division of Medical Image Computing German Cancer Research Center (DKFZ) and Helmholtz Imaging German Cancer Research Center (DKFZ) ESAT-PSI KU Leuven Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University and HIDSS4Health - Helmholtz Information and Data Science School for Health Shanghai Jiao Tong University Shanghai Artificial Intelligence Laboratory Division of Medical Image Computing German Cancer Research Center (DKFZ) Division of Medical Image Computing German Cancer Research Center (DKFZ) and Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Helmholtz Imaging German Cancer Research Center (DKFZ) and Interactive Machine Learning Group (IML) DKFZ School of Computer Science and Engineering Northwestern Polytechnical University Australian Institute for Machine Learning The University of Adelaide College of Computer Science and Technology Zhejiang University Hong Kong University of Science and Technology (Guangzhou) Hong Kong University of Science and Technology (Guangzhou) and Hong Kong University of Science and Technology Faculty of Informatics and Data Science University of Regensburg Faculty of Electrical Engineering and Information Technology RWTH Aachen University Faculty of Informatics and Data Science University of Regensburg and Fraunhofer Institute for Digital Medicine MEVIS Electronic & Information Engineering School Harbin Institute of Technology (Shenzhen) Shanghai Jiao Tong University and Beijing Academy of Artificial Intelligence (BAAI) S

ISBN: (纸本)9798331314385

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and short-term outcome pressure. As a consequence, good performance on standard benchmarks does not guarantee success in real-world scenarios. To address these problems, we present Touchstone, a large-scale collaborative segmentation benchmark of 9 types of abdominal organs. This benchmark is based on 5,195 training CT scans from 76 hospitals around the world and 5,903 testing CT scans from 11 additional hospitals. This diverse test set enhances the statistical significance of benchmark results and rigorously evaluates AI algorithms across out-of-distribution scenarios. We invited 14 inventors of 19 AI algorithms to train their algorithms, while our team, as a third party, independently evaluated these algorithms. In addition, we also evaluated pre-existing AI frameworks—which, differing from algorithms, are more flexible and can support different algorithms—including MONAI from NVIDIA, nnU-Net from DKFZ, and numerous other open-source frameworks. We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain.

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Inducing superconductivity in quantum anomalous Hall regime

arXiv

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arXiv 2024年

作者： Huang, Yu Fu, Yu Zhang, Peng Wang, Kang L. He, Qing Lin International Center for Quantum Materials School of Physics Peking University Beijing100871 China Collaborative Innovation Center of Quantum Matter Beijing100871 China Interdisciplinary Institute of Light-Element Quantum Materials Research Center for Light-Element Advanced Materials Peking University Beijing100871 China Department of Electrical and Computer Engineering Department of Physics and Astronomy Department of Materials Science and Engineering University of California Los AngelesCA90095 United States

Interfacing the quantum anomalous Hall insulator with a conventional superconductor is known to be a promising manner for realizing a topological superconductor, which has been continuously pursued for years. Such a proximity route depends to a great extent on the control of the delicate interfacial coupling of the two constituents. However, a recent experiment reported the failure to reproduce such a topological superconductor, which is ascribed to the negligence of the electrical short by the superconductor in the theoretical proposal. Here, we reproduce this topological superconductor with attention to the interface control. The resulted conductance matrix under a wide magnetic field range agrees with the fingerprint of this topological superconductor. This allows us to develop a phase diagram that unveils three regions parameterized by various coupling limits, which not only supports the feasibility to fabricate the topological superconductor by proximity but also fully explains the origin of the previous debate. The present work provides a comprehensible guide on fabricating the topological superconductor. Copyright © 2024, The Authors. All rights reserved.

关键词： Superconducting materials

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