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arXiv 2025年

作者： Shi, Zhengyuan Ma, Chengyu Zheng, Ziyang Zhou, Lingfeng Pan, Hongyang Jiang, Wentao Yang, Fan Yang, Xiaoyan Chu, Zhufei Xu, Qiang Department of Computer Science and Engineering The Chinese University of Hong Kong Sha Tin Hong Kong Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China School of Computer Science Hangzhou Dianzi University Hangzhou China School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University Shanghai China National Center of Technology Innovation for EDA Nanjing China

Representation learning for post-mapping (PM) netlists is a critical challenge in Electronic design Automation (EDA), driven by the diverse and complex nature of modern circuit designs. Existing approaches focus on intermediate representations like And-Inverter Graphs (AIGs), limiting their applicability to post-synthesis stages. We introduce DeepCell, a multiview representation learning framework that integrates structural and functional insights from both PM netlists and AIGs to learn rich, generalizable embeddings. At its core, DeepCell employs the novel Mask Circuit Modeling (MCM) mechanism, which refines PM netlist representations in a self-supervised manner using pretrained AIG encoders. DeepCell sets a new benchmark in PM netlist representation, outperforming existing methods in predictive accuracy and reconstruction fidelity. To validate its efficacy, we apply DeepCell to functional engineering Change Orders (ECO), achieving significant reductions in patch generation costs and runtime while improving patch quality. Copyright © 2025, The Authors. All rights reserved.

关键词： Mapping

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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GNN-Assisted BiG-AMP: Joint Channel Estimation and Data Detection for Massive MIMO Receiver

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IEEE Transactions on Wireless Communications 2025年

作者： Liu, Zishen Wu, Nan He, Dongxuan Yuan, Weijie Li, Yonghui Quek, Tony Q. S. School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of System Design and Intelligent Manufacturing Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China School of Electrical and Information Engineering The University of Sydney SydneyNSW2008 Australia Singapore University of Technology and Design 487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of

In this paper, we develop a graph neural network (GNN)-assisted bilinear inference approach to enhance the receiver performance of the MIMO system through message passing-based joint channel estimation and data detection (JCD). Specifically, based on the bilinear generalized approximate message passing (BiG-AMP) framework and conditional correlation of signal, we propose a GNN-assisted BiG-AMP (GNN-BiGAMP) approach, which integrates a GNN module into the data-detection-loop to compensate the inaccurate marginal likelihood approximation. By leveraging the coupling between the channel and received symbols, a bilinear GNN-assisted BiG-AMP (BiGNN-BiGAMP) JCD receiver is further proposed. This method incorporates two GNNs with similar graph representation into the bilinear posterior estimation loops, which not only compensates for approximation errors but also alleviates performance loss due to premature variance convergence, thereby enhancing the receiver performance significantly. To fully exploit the supervised information from channel estimation and data detection, we propose a multitask learning based training scheme, which coordinates GNNs with different tasks in two loops. Simulation results show that our proposed GNN-assisted JCD receivers significantly outperform other JCD counterparts in terms of both channel estimation and data detection. © 2025 IEEE. All rights reserved.

关键词： Graph neural networks

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Joint design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

arXiv

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

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High Accuracy Source Localization Based on Parallel Factor Analysis of TDOA in the Cross Correlation Domain

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IEEE Transactions on Communications 2025年

作者： Li, Jianfeng Jiang, Hang Li, Yingying Zhou, Fuhui Wu, Qihui Quek, Tony Q. S. Al-Dhahir, Naofal Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing211106 China Nanjing University of Aeronautics and Astronautics College of Artificial Intelligence Nanjing China Singapore University of Technology and Design Singapore487372 Singapore Yonsei University Yonsei Frontier Laboratory Seoul03722 Korea Republic of University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75080 United States

It is challenging to ensure both high accuracy and low complexity when localizing radiation sources. To address this challenge, we propose two novel methods leveraging time difference of arrival (TDOA) measurements. Specifically, we introduce a TDOA estimation method and a direct position determination (DPD) method based on parallel factor (PARAFAC) analysis in the cross-correlation domain. Initially, multiple sensors synchronously capture the source signal, and the cross-correlation function between signals received from a reference sensor and other sensors is calculated. Then, the primary cross-spectrum data undergoes an expansion and integration process to establish the PARAFAC model. Through cross-spectrum expansion, virtual nodes are formed, which further improves the estimation performance. The TDOA estimates for each sensor are obtained by normalizing and extracting the phase from this matrix. Additionally, we introduce a novel DPD method tailored for multipath propagation scenarios. Simulations and real-world measurements demonstrate the superiority and effectiveness of our proposed methods compared with cutting-edge methods. © 1972-2012 IEEE.

关键词： Time difference of arrival

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A novel integrated ultraviolet photodetector based on standard CMOS process

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Chinese Physics B 2015年第3期24卷 418-422页

作者：汪涵金湘亮陈长平田满芳朱柯翰 Faculty of Materials Optoelectronics and PhysicsXiangtan University Hunan Engineering Laboratory for Microelectronics Optoelectronics and System on a Chip Electrical and Computer Engineering Department Boise State University

A novel integrated ultraviolet（UV） photodetector has been proposed, which realizes a high UV selectivity by combining a conventional UV-selective photodiode with an extra infrared（IR） photodiode. The IR photodiode is designed for compensating the photocurrent response of the UV photodiode in the infrared band and is 15 times smaller than the UV one. The integrated photodetector has been fabricated in a 0.35 μm standard CMOS technology. Some critical performance indices of this new structure photodetector, such as spectral responsivity, breakdown voltage, quenching waveform, and transient response, are measured and analyzed. Test results show that the complementary UV–IR photodetector has a maximum spectral responsivity of 0.27 A·W-1 at the wavelength of 400 nm. The device has a high UV selectivity of 3000,which is much higher than that of the single UV photodiode.

关键词： ultraviolet photodetector compensating parasitic photocurrent UV selectivity CMOS process

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Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints 23

Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

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Proceedings of the 60th Annual ACM/IEEE design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Center for Discrete Mathematics Fuzhou University Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

关键词： escape routing

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Energy diffusion model of bR for voxel identification

Energy diffusion model of bR for voxel identification

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2005 IEEE International 48th Midwest Symposium on Circuits and systems, MWSCAS 2005

作者： Neto, Didimo Garcia Abdel-Aty-Zohdy, Hoda S. Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester United States

ISBN: (纸本)0780391977

In this paper, a potential biological structure for computer volumetric memory is investigated. Bacteriorhodopsin is a protein found in the purple membrane of the bacteria Halobacterium salinarum. This protein has light absorption properties that generate different stable states allowing the use of multi-level logic as well as binary logic. CHARMm™ has been used to simulate the energy response of Bacteriorhodopsin at room temperature 300K for the bR ground state and the other states. The K state takes place after blue light (λ= 635nm) absorption on the bR state. The energy difference is found to be an increase of 1086.92 kcal/mol which is responsible for triggering the photocycle that also includes the states K, L, M, N, and O. An energy surplus is found between 6 and bR state that may be spread to surrounding molecules. However, conformational interference will not produce photons necessary for the isomerization reaction. Further Quantum Molecular (QM) analysis should provide an extended model for this macromolecular energy study. © 2005 IEEE.

关键词： Storage allocation (computer)

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Wafer-Scale Synthesis of WS_(2)Films with In Situ Controllable p-Type Doping by Atomic Layer Deposition

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Research 2021年第1期2021卷 1424-1432页

作者： Hanjie Yang Yang Wang Xingli Zou Rongxu Bai Zecheng Wu Sheng Han Tao Chen Shen Hu Hao Zhu Lin Chen David W.Zhang Jack C.Lee Xionggang Lu Peng Zhou Qingqing Sun Edward T.Yu Deji Akinwande Li Ji State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai 200433China State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China Microelectronics Research Center Department of Electrical and Computer EngineeringThe University of Texas at AustinAustin78758 TexasUSA

Wafer-scale synthesis of p-type TMD films is critical for its commercialization in next-generation electro/*** this work,wafer-scale intrinsic n-type WS_(2)films and in situ Nb-doped p-type WS_(2)films were synthesized through atomic layer deposition(ALD)on 8-inchα-Al_(2)O_(3)/Si wafers,2-inch sapphire,and 1 cm^(2)GaN substrate *** Nb doping concentration was precisely controlled by altering cycle number of Nb precursor and activated by ***_(2)n-FETs and Nb-doped p-FETs with different Nb concentrations have been fabricated using CMOS-compatible processes.X-ray photoelectron spectroscopy,Raman spectroscopy,and Hall measurements confirmed the effective substitutional doping with *** on/off ratio and electron mobility of WS_(2)n-FET are as high as 105 and 6.85 cm^(2)V^(-1)s^(-1),*** WS_(2)p-FET with 15-cycle Nb doping,the on/off ratio and hole mobility are 10 and 0.016 cm^(2)V^(-1)s^(-1),*** p-n structure based on n-and p-type WS_(2)films was proved with a 10^(4)rectifying *** realization of controllable in situ Nb-doped WS_(2)films paved a way for fabricating wafer-scale complementary WS_(2)FETs.

关键词： sapphire doping realization

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Knowledge diffusion through experiential education, focusing on robotic technologies, virtual reality and internet of things 24

Knowledge diffusion through experiential education, focusing...

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24th Pan-Hellenic Conference on Informatics, PCI 2020

作者： Spournias, Alexandros Faliagka, Evanthia P. Antonopoulos, Christos S. Voros, Nikolaos Embedded System Design and Applications Laboratory Electrical and Computer Engineering Department University of Peloponnese Greece

ISBN: (纸本)9781450388979

This work proposes a new and innovative approach to the knowledge diffusion, through experiments as well as experiential training, focusing on cutting-edge technologies. These technologies refer to robotic technologies, virtual reality, cyberphysical systems and the Internet of Things, always under the prism of open source and open access approaches. For the diffusion of these technologies, ESDA Lab provides an environment with the infrastructure that supports these technologies creating a living experimental laboratory ecosystem. © 2020 ACM.

关键词： Internet of things

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