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An Image Semantic Communication system Based on GAN and Relative Position-Encoding

IEEE Communications Letters 2025年

作者： Zhang, Ziqi Tan, Weijie Li, Chunguo Guizhou University College of Big Data and Information Engineering Guiyang550025 China Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610025 China Ministry of Industry and Information Technology Laboratory of Cryptography Application Technology Innovation and Testing Verification Beijing100015 China Southeast University School of Information Science and Engineering Nanjing210096 China

In image semantic communication, the complex wireless channel environment leads to the loss of image details and performance degradation during transmission. To address this issue, we propose an image semantic communication system based on Generative Adversarial Networks (GAN) and Relative Position-Encoding (RPE), named GAN-RpeSC. Specifically, in the system design, we introduce the GAN network at the output of the semantic communication framework to enhance the image restoration. We integrate the RPE module into the Visual Transformer (ViT) module, adding the RPE module to its Multihead Self Attention (MHSA), so that the model can better capture the spatial location information of the image. Experimental results show that the proposed GAN-RpeSC has significant advantages in improving image transmission quality, with a 0.3 dB improvement in peak signal-to-noise ratio (PSNR) compared to the ViT module alone. © 1997-2012 IEEE.

关键词： Encoding (symbols)

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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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Approximation Methods for Simulation and Equivalence Checking of Noisy Quantum Circuits

arXiv

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arXiv 2025年

作者： Huang, Mingyu Guan, Ji Fang, Wang Ying, Mingsheng Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing101408 China School of Informatics University of Edinburgh EdinburghEH8 9UR United Kingdom Centre for Quantum Software and Information University of Technology Sydney UltimoNSW2007 Australia

In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise representations, constraining simulation, and equivalence checking to circuits with a limited number of qubits. This paper introduces an approximation algorithm for simulating and assessing the equivalence of noisy quantum circuits, specifically designed to improve scalability under low-noise conditions. The approach utilizes a novel tensor network diagram combined with singular value decomposition to approximate the tensors of quantum noises. The implementation is based on Google’s TensorNetwork Python package for contraction. Experimental results on realistic quantum circuits with realistic hardware noise models indicate that our algorithm can simulate and check the equivalence of QAOA (Quantum Approximate Optimization Algorithm) circuits with around 200 qubits, surpassing the state-of-the-art methods by noise number and execution time. © 2025, CC BY.

关键词： Qubits

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A New Paradigm of User-Centric Wireless Communication Driven by Large Language Models

arXiv

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arXiv 2025年

作者： Ding, Kuiyuan Guo, Caili Yang, Yang Hu, Wuxia Eldar, Yonina C. Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Beijing Laboratory of Advanced Information Net works School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

The next generation of wireless communications seeks to deeply integrate artificial intelligence (AI) with user-centric communication networks, with the goal of developing AI-native networks that more accurately address user requirements. The rapid development of large language models (LLMs) offers significant potential in realizing these goals. However, existing efforts that leverage LLMs for wireless communication often overlook the considerable gap between human natural language and the intricacies of real-world communication systems, thus failing to fully exploit the capabilities of LLMs. To address this gap, we propose a novel LLM-driven paradigm for wireless communication that innovatively incorporates the nature language to structured query language (NL2SQL) tool. Specifically, in this paradigm, user personal requirements is the primary focus. Upon receiving a user request, LLMs first analyze the user intent in terms of relevant communication metrics and system parameters. Subsequently, a structured query language (SQL) statement is generated to retrieve the specific parameter values from a high-performance real-time database. We further utilize LLMs to formulate and solve an optimization problem based on the user request and the retrieved parameters. The solution to this optimization problem then drives adjustments in the communication system to fulfill the user’s requirements. To validate the feasibility of the proposed paradigm, we present a prototype system. In this prototype, we consider user-request centric semantic communication (URC-SC) system in which a dynamic semantic representation network at the physical layer adapts its encoding depth to meet user requirements, such as improved data transmission quality or reduced data transmission latency. Additionally, two LLMs are employed to analyze user requests and generate SQL statements, respectively. Simulation results demonstrate the effectiveness of the prototype in personalizing and addressing user r

关键词： Structured Query Language

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TDiffSal: Text-Guided Diffusion Saliency Prediction Model for Images 27th

TDiffSal: Text-Guided Diffusion Saliency Prediction Model fo...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhang, Nana Xiong, Min Zhu, Dandan Zhu, Kun Zhai, Guangtao School of Computer Science and Technology Donghua University No. 2999 Renmin North Road Songjiang District Shanghai201620 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Institute of AI Education Shanghai East China Normal University No. 3663 Zhongshan North Road Putuo District Shanghai200333 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University No. 4800 Cao’an Highway Jiading District Shanghai201804 China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University No. 800 Dongchuan Road Minhang District Shanghai200240 China

ISBN: (纸本)9783031781858

Existing visual saliency prediction methods mainly focus on single-modal visual saliency prediction, while ignoring the significant impact of text on visual saliency. To more comprehensively explore the influence of text on human attention in images, we propose a text-guided diffusion saliency prediction model, named TDiffSal. In specific, recent studies on stable diffusion models have shown promising performance in unifying tasks due to their inherent generalization ability. Inspired by this, a novel diffusion model for generalized visual-text saliency prediction is proposed, which formulates the prediction issue as a conditional generative task of the saliency map by employing input visual and text as the conditions. Meanwhile, we introduce a multi-head fusion module to effectively integrate text features and image features, which can efficiently guide the image denoising process and progressively refine the generated saliency map to make it semantically relevant to the text. Additionally, we employ an efficient pre-training strategy to enhance the robustness and generalization of the proposed model. We conduct extensive experiments on benchmark datasets to demonstrate its superior performance compared to other state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Prediction models

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SatCooper: Enhancing Cooperative Inference Analytics for Satellite Service via Multi-exit DNNs

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IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Qiyang Wang, Shangguang Guan, Jinglong Donta, Praveen Kumar Ma, Xiao Prasad, RangaRao Venkatesha Dustdar, Schahram Liu, Xuanzhe Peking University School of Computer Science Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Stockholm University Department of Computer and Systems Sciences Kista16455 Sweden Beiyou Shenzhen Institute Shenzhen China Netherlands TU Wien Distributed System Group Wien1040 Austria UPF Barcelona Spain

As a key technology of intelligent satellite-enabled services in B5G or 6G networks, deploying Deep Neural Networks (DNN) models on satellites has been a notable trend, catering to the daily demand for extensive computing-intensive and latency-sensitive tasks. The computing resources are strategically deployed on satellites where sensor data is generated or collected, facilitating the fine-grained computational inference of DNN-based tasks. However, no prior study has comprehensively explored the crucial inference challenges-e.g., the trade-off between the number of tasks completed and accuracy and partitioning models in multi-exit models-in the resource-constrained space environment. Effective scheduling frameworks cater to various streams of inference tasks are scarce because inference performance may deviate from the ideal situation due to changes in task system status, such as task profiles and network state. To this end, we first formulate a gain-aware in-orbit computing inference problem to strike a proper trade-off between inference latency and the number of tasks completed by dynamically selecting optimal early exit points and model partitioning points. We propose an offline dynamic programming-based algorithm that provides an effective solution when comprehensive system details are to be predicted. We have developed an online learning-based method to schedule inference tasks with uncertain and dynamic system statuses in real-world situations. Our evaluation shows that, compared to baseline methods, the online learning-based algorithm can improve task gain by an average of 87.3% across various tasks. © 2002-2012 IEEE.

关键词： Dynamic programming

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SimK:A Large-Scale Parallel Simulation Engine

引用

Journal of computer Science & Technology 2009年第6期24卷 1048-1060页

作者：许建卫陈明宇郑规曹政吕慧伟孙凝晖 Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Simulation is an important method to evaluate future computer systems. Currently microprocessor architecture has switched to parallel, but almost all simulators remained at sequential stage, and the advantages brought by multi-core or many-core processors cannot be utilized. This paper presents a parallel simulator engine （SimK） towards the prevalent SMP/CMP platform, aiming at large-scale fine-grained computer system simulation. In this paper, highly efficient synchronization, communication and buffer management policies used in SimK are introduced, and a novel lock-free scheduling mechanism that avoids using any atomic instructions is presented. To deal with the load fluctuation at light load case, a cooperated dynamic task migration scheme is proposed. Based on SimK, we have developed large-scale parallel simulators HppSim and HppNetSim, which simulate a full supercomputer system and its interconnection network respectively. Results show that HppSim and HppNetSim both gain sound speedup with multiple processors, and the best normalized speedup reaches 14.95X on a two-way quad-core server.

关键词： large scale system simulation fine-grained synchronization simulation framework lock-free synchronization

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Improved High-Speed Thermal Analysis Based on Two-Step Simulation for High-Frequency Transformers

Improved High-Speed Thermal Analysis Based on Two-Step Simul...

引用

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

作者： Zheyuan Yi Kai Sun Qiang Li Zengyang Liu Department of Electrical Engineering State Key Laboratory of Power System Tsinghua University Beijing China Delta Electronics Shanghai Co. Ltd. Shanghai China The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State Center for Power Electronics Systems University Blacksburg Virginia USA

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

Thermal analysis is a crucial and time-consuming step in the optimization design process of high-frequency transformers (HFTs). This paper proposes an improved thermal analysis method based on heat dissipation-conduction two-step simulation, significantly reducing the computation time while ensuring the accuracy of thermal analysis. Simulation results validate the accuracy and of the proposed method and demonstrate that the proposed method saves 82% of computation time for a single thermal analysis case compared to direct CFD. Experimental results further verify the accuracy of the proposed method. An exemplary application of the proposed method in the optimization design of the HFT illustrates a 98% reduction in computation time for thermal analysis during the optimization process.

关键词： Heating systems Temperature distribution Accuracy Simulation Computational modeling Thermal analysis High-frequency transformers Optimization Surface treatment Heat transfer

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Revisiting the interplay between Comammox and Anammox: cooperative or competitive?

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Journal of Water Process Engineering 2025年 75卷

作者： Bian, Yihao Fu, Kunming He, Xun Li, Xiaodan Wang, Xinlin Zhang, Yongji State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai 200092 China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092 China Key Laboratory of Urban Storm Water System and Water Environment Ministry of Education Beijing University of Civil Engineering and Architecture Beijing 100044 China

Complete ammonia oxidation (Comammox) has challenged the traditional two-step nitrification paradigm and reshaped the understanding of nitrogen removal in wastewater treatment. Anaerobic ammonia oxidation (Anammox) technology is considered as a suitable process for future wastewater treatment. However, the limited availability of substrates for Anammox has consistently hindered its broader application. The Comammox process has often been neglected in previous studies of Anammox. However, as far as the current study is concerned, Comammox may contribute to the advancement of wastewater treatment in the future with its wide distribution, strong environmental adaptability and low greenhouse-gas emissions. Recent studies have shown that Comammox may have the ability of nitrite leakage during ammonia oxidation, which provides a new pathway for substrate acquisition for the Anammox process. In this study, the relationship between Comammox and Anammox was elaborated based on their functions by comparing the distribution of both, as well as the similarity and specificity of the effects of different environmental factors on them. It was noted that the synergistic effects of Comammox and Anammox should be further explored. A possible strategy to achieve a fast nitrite supply by Comammox is proposed and the optimization of kinetic parameters is suggested. © 2025 Elsevier Ltd

关键词： Anammox Comammox N2O Nitrification Nitrite

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Predicting on the Extreme Precipitation in East and Southeast Asia during Summer 2022 from the Antecedent Soil Temperature Anomaly over the Tibetan Plateau

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Journal of Climate 2025年第9期38卷 2109-2128页

作者： Kong, Xianghui Wang, Aihui Xue, Yongkang Wei, Nan Zhang, He Hu, Qin He, Juanxiong Bi, Xunqiang Chen, Yue Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China Plateau Atmosphere and Environment Key Laboratory of Sichuan Province Chengdu University of Information Technology Sichuan Province Chengdu China University of California Los AngelesCA United States School of Atmospheric Sciences Sun Yat-sen University Zhuhai China International Center for Climate and Environment Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China School of Atmospheric Sciences Chengdu University of Information Technology Sichuan Province Chengdu China Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China National Super Computer Center in Tianjin Tianjin China State Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China

It has demonstrated that May land surface temperature (LST) and subsurface temperature (SUBT) anomalies on the Tibetan Plateau (TP) can serve as a predictor of June precipitation in downstream *** summer 2022, there was heavy precipitation (severe drought) in June (August) over southern China, coinciding with high May (July) LST/SUBT anomalies in *** the framework of the Impact of Initialized Land Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P), this study explores the causality between 2022 May (July) TP LST/SUBT and June (August) precipitation using an ensemble of land–atmosphere coupled model *** show that model prediction with imposed strongly positive May TP LST/SUBT (i.e., a triple) anomaly could produce 67% (46%) of June precipitation anomalies in South (northeast) China, while sea surface temperature (SST) effects account for 5% (51%).The atmosphere condensation heating and surface sensible heating due to TP LST/SUBT anomaly induce anomalous South Asian high, which moves eastward along with the Rossby ***, the above process enhances upward motion, convective instability, and water vapor transport, eventually be favorable for rainfall formation in South China and northeast *** Southeast Asia, it makes a downward movement, decrease in atmospheric water vapor, and unfavorable to the occurrence of ***, July TP LST/SUBT contributes to the prediction skill for August record-breaking drought in southern *** to SST effects, it is found that TP LST/SUBT effects significantly enhance the prediction skill for downstream region, suggesting that the TP land contributes an important source for subseasonal climate prediction. © 2025 American Meteorological Society.

关键词： Rivers

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