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OFDM-structure based waveform designs for integrated sensing and communication

Science China(Information Sciences) 2025年第5期68卷 267-284页

作者： Jiaqi LIU Ping YANG Ke JIANG Jiarong ZHAO Wei XIANG Jianping WEI Ruixiang DUAN Saviour ZAMMIT Tony Q.S.QUEK National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China School of Computing Engineering and Mathematical Sciences La Trobe University Meituan Academy of Robotics Department of Communications and Computer Engineering University of Malta Information Systems Technology and Design Pillar Singapore University of Technology and Design

The future sixth-generation(6G) paradigm aims to seamlessly integrate communication and environmental sensing capabilities into a single radio signal, promising improved efficiency and cost-effectiveness through simultaneous data communications and environmental perception. At the core of this evolution, orthogonal frequency division multiplexing(OFDM) and its advanced waveforms emerge as pivotal for integrated sensing and communications(ISAC). This study introduces a concise and unified ISAC waveform design framework based on orthogonal multicarriers. This framework supports versatile applications of OFDM and its derivative waveforms within a generalized ISAC system, marking a significant leap in integrating communication and sensing capabilities. A distinguishing feature of this framework is its adaptability,allowing users to intelligently select modulation strategies based on their specific environmental needs. This adaptability optimizes performance across diverse scenarios. Central to our innovations is the proposal of discrete Fourier transformspread OFDM with index modulation(DFT-S-OFDM-IM). This framework is paired with newly proposed signal processing methods for single-input single-output and multiple-input multiple-output(MIMO) systems. Extensive evaluations highlight DFT-S-OFDM-IM's superiority, including dramatically reduced peak-to-average power ratios(PAPRs), competitive communication performance, and exceptional sensing capabilities, striking an elegant balance between communication capacity and environmental sensing precision.

关键词： DFT-S-OFDM-IM index modulation integrated sensing and communication OFDM

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Loop Vectorization Optimization Technique for System Calls 25

Loop Vectorization Optimization Technique for System Calls

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Proceedings of the 2025 5th International Conference on Computer Network Security and Software engineering

作者： Lili Liu Jinyang Yao Wenbo Liu Chaowei Zhao Yingying Li Jinlong Xu Ping Zhang Bo Zhao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (纸本)9798400713613

With the continuous advancement of modern processor architectures, SIMD (Single Instruction Multiple Data) vectorization has become one of the key techniques for improving program performance. Loop vectorization, as a core technique of SIMD optimization, can significantly enhance the execution efficiency of loop code with data parallelism. However, in practical applications, many loops contain system calls (such as printf), which often introduce side effects or uncertainties in control flow. This leads traditional compilers to adopt a conservative strategy during loop vectorization, avoiding vectorizing the entire loop. While this strategy helps prevent potential execution errors, it also leaves many loops with vectorization potential under-optimized. To address this issue, this paper proposes a loop vectorization optimization technique for loops containing system calls. By introducing directive-based guidance and appropriate handling mechanisms, the proposed method allows the compiler to identify and effectively process loops with system calls, enabling successful vectorization. Specifically, programmers can guide the compiler to selectively vectorize these loops as needed, maximizing performance improvements while ensuring program correctness. By precisely controlling which parts of the code can be vectorized and which must preserve their original execution order, this method effectively solves the problem of non-vectorizable loops with system calls, significantly improving program execution efficiency. To evaluate the effectiveness of the proposed method, we designed 24 test cases containing system calls. Experimental results show that, the highest optimization level (O3) of the compiler, the proposed method achieved an average speedup of 1.4677×. Further analysis indicates that as the ratio of computational instructions to system call instructions increases, the speedup generally rises, despite some fluctuations.

关键词： Loop vectorization

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Meta Transductive Linear Probing for Few-Shot Node Classification

Meta Transductive Linear Probing for Few-Shot Node Classific...

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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on

作者： Mingjing Lan Ningbo Huang Gang Zhou Yi Xia State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Graph few-shot learning aims to predict well by training with very few labeled data. Meta learning has been the most popular solution for few-shot learning problem. However, transductive linear probing shows that fine-tuning a simple linear classification head after a pretrained graph neural networks can outperforms most of the sophisticated-designed graph meta learning algorithms. Therefore, in the paper, we propose a meta transductive linear probing methods named Meta-TLP to incorporate the advantages of graph self-supervised and graph meta learning model. Specifically, the graph neural network is firstly pretrained with graph contrastive learning methods. Then we design an unsupervised meta training task construction methods to require meta tasks without relying on labeled data. Finally, we meta training the linear classification head on the meta training tasks to learn to fast adopt to novel classes. Experiment results show that our model can perform better than TLP on three real world datasets.

关键词： Training Metalearning Design methodology Data visualization Prediction algorithms Magnetic heads Data models Graph neural networks Pattern recognition Few shot learning

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Recent progress of iron-based electrocatalysts for nitrogen reduction reaction

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Journal of Materials Science & Technology 2023年第9期140卷 121-134页

作者： Tianyi Wang Zhongyuan Guo Xiaoli Zhang Qinye Li Aimin Yu Chengzhang Wu Chenghua Sun Department of Chemistry and Biotechnology School of ScienceComputing and Engineering TechnologiesSwinburne University of TechnologyHawthornVIC3122Australia School of Material Science and Engineering Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Advanced Special Steel Shanghai Key Laboratory of Advanced FerrometallurgySchool of Materials Science and EngineeringShanghai UniversityShanghai 200444China

Ammonia is a critical feedstock for modern industry and agriculture,which is also a promising carbonfree energy *** nitrogen reduction reaction(ENRR)is a sustainable and efficient approach to synthesize ammonia under ambient reaction *** relies on the development of highly efficient *** far various strategies have been applied to enhance the performance of catalysts including tuning the electronic structure,binding strength,coordination configuration as well as the introduction of multiple active sites and *** this review,the recent progress of Fe-based electrocatalysts and their coordination effect,syner gistic effect and def ect effect for nitrogen reduction reaction have been *** critical review focuses on the discussion of theoretical advancement,the performance origin of ENRR activity and selectivity of Fe-based electrocatalysts.

关键词： effect coordination critical

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A GAN-based Method for Generating SQL Injection Attack Samples 10

A GAN-based Method for Generating SQL Injection Attack Sampl...

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10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Lu, Dongzhe Fei, Jinlong Liu, Long Li, Zecun Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

Due to the simplicity of implementation and high threat level, SQL injection attacks are one of the oldest, most prevalent, and most destructive types of security attacks on Web-based information systems. With the continuous development and maturity of artificial intelligence technology, it has been a general trend to use AI technology to detect SQL injection. The selection of the sample set is the deciding factor of whether AI algorithms can achieve good results, but dataset with tagged specific category labels are difficult to obtain. This paper focuses on data augmentation to learn similar feature representations from the original data to improve the accuracy of classification models. In this paper, deep convolutional generative adversarial networks combined with genetic algorithms are applied to the field of Web vulnerability attacks, aiming to solve the problem of insufficient number of SQL injection samples. This method is also expected to be applied to sample generation for other types of vulnerability attacks. © 2022 IEEE.

关键词： Generative adversarial networks

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IBM Small-Scale Superconducting Quantum Computer Not Gate Error Test

IBM Small-Scale Superconducting Quantum Computer Not Gate Er...

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2021 International Conference on Electronic Communication, Computer Science and Technology, ECCST 2021

作者： He, Ming Liu, Xiaonan Wang, Junchao An, Jiale State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Henan Zhengzhou450001 China

Quantum NOT gates play an important role in the process of quantum information conversion. However, when the X-gate operation is executed on a real quantum computer, there is a large deviation between the actual operation result and the theory, which will lead to inaccurate results when the quantum algorithm containing the X-gate operation is executed. In order to facilitate users to understand the error fluctuations of the X gate in time before executing the quantum algorithm containing the X gate operation on the IBM quantum cloud platform, this paper proposes a method to measure the X gate error. By measuring the X-gate error of four small-scale superconducting quantum computers on the back end of the IBM quantum cloud platform, analyze the degree of fluctuation of the actual measurement value of the quantum device;at the same time, under different execution times shots, the influence of the X-gate test is analyzed. The test results show that the measured value of each qubit of different quantum devices fluctuates to different degrees;the execution times of shots are different, and the test results of X-gate error will be affected to different degrees. This test method helps users select the optimal performance of the qubits before executing quantum algorithms with X gate on IBM's small-scale quantum computers. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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An algorithm/hardware co-optimized method to accelerate CNNs with compressed convolutional weights on FPGA

An algorithm/hardware co-optimized method to accelerate CNNs...

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作者： Shang, Jiangwei Zhang, Zhan Zhang, Kun Li, Chuanyou Qian, Lei Liu, Hongwei School of Computer Science and Technology Harbin Institute of Technology Harbin China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China School of Computer Science and Engineering Southeast University Nanjing China

Convolutional neural networks (CNNs) have shown remarkable advantages in a wide range of domains at the expense of huge parameters and computations. Modern CNNs still tend to be more complex and larger to achieve better inference accuracy. However, the complex and large structures of CNNs could slow down the inference speed. Recently, Compressing the convolutional weights to be sparse by pruning the unimportant parameters has been demonstrated as an efficient way to reduce the computations of CNNs. On the other hand, field-programmable gate arrays (FPGAs) have been a popular hardware platform to accelerate CNN inference. In this paper, we propose an algorithm/hardware co-optimized method for accelerating CNN inference on FPGAs. For the algorithm, we take advantage of unstructured and structured parameter sparsifying methods to achieve high sparsity and keep the regularity of convolutional weights. Correspondingly, hardware-friendly index representations of sparse convolutional weights are proposed. For the hardware architecture, we propose row-wise input-stationary dataflow, which is tightly coupled with the algorithm. A row-wise computing engine (RConv Engine) is proposed, which is based on the dataflow. Inside the RConv Engine, the scalar-vector structure is applied to implement the basic processing elements (PEs). To flexibly calculate the feature map with various sizes, the PEs are organized in a 2D structure with two work modes. The experimental results demonstrate that our co-optimized method implements high sparsity of convolutional weights, and the computing engine achieves high computation efficiency. Compared with other accelerators, our co-optimized method implements a 10.9 (Formula presented.) speedup on FPS at most with the highest sparsity of convolutional weights and negligible accuracy loss. © 2024 John Wiley & Sons Ltd.

关键词： Engines

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Byzantine-robust distributed support vector machine

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Science China Mathematics 2025年第3期68卷 707-728页

作者： Xiaozhou Wang Weidong Liu Xiaojun Mao School of Statistics East China Normal UniversityShanghai 200062China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(Ministry of Education) East China Normal UniversityShanghai 200062China School of Mathematical Sciences Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Artificial Intelligence(Ministry of Education) Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Scientific and Engineering Computing(Ministry of Education) Shanghai Jiao Tong UniversityShanghai 200240China

The development of information technology brings diversification of data sources and large-scale data sets and calls for the exploration of distributed learning algorithms. In distributed systems, some local machines may behave abnormally and send arbitrary information to the central machine(known as Byzantine failures), which can invalidate the distributed algorithms based on the assumption of faultless systems. This paper studies Byzantine-robust distributed algorithms for support vector machines(SVMs) in the context of binary classification. Despite a vast literature on Byzantine problems, much less is known about the theoretical properties of Byzantine-robust SVMs due to their unique challenges. In this paper, we propose two distributed gradient descent algorithms for SVMs. The median and trimmed mean operations in aggregation can effectively defend against Byzantine failures. Theoretically, we show the convergence of the proposed estimators and provide the statistical error rates. After a certain number of iterations, our estimators achieve near-optimal rates. Simulation studies and real data analysis are conducted to demonstrate the performance of the proposed Byzantine-robust distributed algorithms.

关键词： Byzantine robustness convergence distributed learning support vector machine

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Synergistically enhanced dielectric, insulating and thermally conductive performances of sandwich PMMA based dielectric films

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Progress in Natural Science:Materials International 2024年第3期34卷 591-597页

作者： Dongmei Zhang Yufan Li Yuchao Li Zhonggui Sun Hanxue Zhu Lujia Yang Yanhu Zhan Yankai Li Shi Wang Jun-Wei Zha School of Mathematical Sciences Liaocheng University School of Materials Science and Engineering Liaocheng University State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications School of Chemistry and Biological Engineering University of Science and Technology Beijing

A tri-layered(B-G-B) dielectric films were simply prepared by alternatively spin-coating boron nitride/polymethylmethacrylate(BN/PMMA, B) and graphene nanosheets(GNS/PMMA, G) compound solutions. The structure, morphology, thermal conductivity, and particularly the dielectric and relaxation behaviors were systematically studied. Results showed that a good exfoliation and dispersion of BN and GNS can be simply achieved through intensive mechanical compounding with PMMA in the internal mixer. The dielectric constant and breakdown strength of the obtained 1-3-1(B-G-B) sandwich composite film reached 4.3(@1 kHz) and 458.6kV/mm, being 119 % and 113 % higher than that of pure PMMA, respectively. Furthermore, the overall thermal conductivity of sandwich 1-3-1 composite increased by 112 % due to the addition of thermally conductive BN and GNS. The sandwich design strategy provided an effective way of achieving good permittivity, high insulation, and improved thermal conductivity simultaneously, showing potential applications in the miniaturization and integration of electronic devices.

关键词： Sandwich structure Breakdown strength Thermal conductivity Dielectric constant Composites

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On Isodual Double Toeplitz Codes

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Journal of Systems Science & Complexity 2024年第5期37卷 2196-2206页

作者： SHI Minjia XU Li SOLÉ Patrick Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China CNRS University of Aix MarseilleCentrale MarseilleI2MMarseille 13284France

Double Toeplitz(shortly DT)codes are introduced here as a generalization of double circulant *** authors show that such a code is isodual,hence formally self-dual(FSD).FSD codes form a far-reaching generalization of self-dual codes,the most important class of codes of rate ***-dual DT codes are characterized as double circulant or double ***,even binary DT codes are characterized as double *** examples obtained by exhaustive search show that the codes constructed have best-known minimum distance,up to one unit,amongst formally self-dual codes,and sometimes improve on the known *** q=2,the authors find four improvements on the best-known values of the minimum distance of FSD *** F4 an explicit construction of DT codes,based on quadratic residues in a prime field,performs equally *** authors show that DT codes are asymptotically good over ***,the authors construct DT codes arbitrarily close to the asymptotic Varshamov-Gilbert bound for codes of rate one half.

关键词： Double circulant codes double Toeplitz codes isodual codes formally self-dual codes

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