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Near-field wideband beam training for ELAA with uniform circular array

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Science China(information Sciences) 2024年第6期67卷 370-383页

作者： Yuhao CHEN Linglong DAI Department of Electronic Engineering Tsinghua UniversityBeijing National Research Center for Information Science and Technology (BNRist)

Extremely large-scale antenna array(ELAA) at millimeter wave(mmWave) and Terahertz(THz)band has been considered a key technology for combating high attenuation in high-frequency bands in future6G communications. Uniform circular arrays(UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing(FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDFbased beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.

关键词： extremely large-scale antenna array (ELAA) uniform circular array (UCA) near-field wideband beam training

Geometry characteristics and wide temperature behavior of silicon-based GaN surface acoustic wave resonators with ultrahigh quality factor

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Science China(information Sciences) 2024年第2期67卷 267-278页

作者： Guofang YU Renrong LIANG Haiming ZHAO Lei XIAO Jie CUI Yue ZHAO Wenpu CUI Jing WANG Jun XU Jun FU Tianling REN School of Integrated Circuits Tsinghua University Beijing National research center for information Science technology Tsinghua University

Surface acoustic wave(SAW) resonators with an ultrahigh Q-factor are designed and fabricated on silicon-based gallium nitride(GaN/Si). The temperature-dependent performance is characterized over a wide range, from 10 to 500 K. Finite element analysis is employed to guide the design of the SAW resonator from indications of the Rayleigh mode and weak propagation direction dependence of SAW in the c-plane of GaN/Si. The SAW resonator with 100 pairs of interdigital transducers(IDT), 100 pairs of grating reflectors(GR) for each side, aperture size of 80 μm, metallization ratio of 0.5, and electrode width of 500 nm resonates at 1.9133 GHz accordingly with an ultrahigh Q-factor of 7622 at room temperature, which contributes the fr× Qr, up to 14.583×1012Hz. A resonator operating over 10 to 500 K indicates an approximately linear decreasing temperature dependence above 280 K while being approximately constant below 40 K. The fitting to resonator characteristics using the modified Butterworth Van Dyke(m BVD) model reveals a reduction in both the electrode and mechanical losses while worsening the dielectric loss with cooling down.

关键词： GaN/Si SAW resonator ultrahigh Q-factor temperature-dependent performance mBVD losses

Constructing the Impossible Differential of Type-II GFN with Boolean Function and Its Application to WARP

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Chinese Journal of Electronics 2024年第1期33卷 80-89页

作者： Jiali SHI Guoqiang LIU Chao LI College of Liberal Arts and Sciences National University of Defense Technology Hunan Engineering research center of Commercial Cryptography Theory and technology Innovation State Key Laboratory of information Security Institute of Information Engineering

Type-Ⅱ generalized Feist el network(GFN) has attracted a lot of attention for its simplicity and high *** differential attack is one of the powerful cryptanalytic approaches for word-oriented block ciphers such as Feistel-like *** deduce the impossible differential of Type-Ⅱ GFN by analyzing the Boolean function in the middle *** main idea is to investigate the expression with the variable representing the plaintext(ciphertext) difference words for the internal state *** adopting the miss-in-the-middle approach,we can construct the impossible differential of Type-Ⅱ *** an illustration,we apply this approach to WARP,a lightweight 128-bit block cipher with a 128-bit key which was presented by Banik et *** SAC *** structure of WARP is a 32-branch Type-Ⅱ ***,we find two 21-round truncated impossible differentials and implement a 32-round key recovery attack on *** the 32-round key recovery attack on WARP,some observations are used to mount an effective *** the advantage of the early abort technique,the data,time,and memory complexities are 2125.69chosen plaintexts,2126.6832-round encryptions,and 2100-bit,*** the best of our knowledge,this is the best attack on WARP in the single-key scenario.

关键词： Ciphers Boolean functions Parallel processing Complexity theory

Understanding adversarial attacks on observations in deep reinforcement learning

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Science China(information Sciences) 2024年第5期67卷 69-83页

作者： You QIAOBEN Chengyang YING Xinning ZHOU Hang SU Jun ZHU Bo ZHANG Department of Computer Science and technology Beijing National Research Center for Information Science and Technology Tsinghua-Bosch Joint Center for Machine Learning Institute for Artificial Intelligence Tsinghua University Peng Cheng Laboratory

Deep reinforcement learning models are vulnerable to adversarial attacks that can decrease the cumulative expected reward of a victim by manipulating its observations. Despite the efficiency of previous optimization-based methods for generating adversarial noise in supervised learning, such methods might not achieve the lowest cumulative reward since they do not generally explore the environmental ***, a framework is provided to better understand the existing methods by reformulating the problem of adversarial attacks on reinforcement learning in the function space. The reformulation approach adopted herein generates an optimal adversary in the function space of targeted attacks, repelling them via a generic two-stage framework. In the first stage, a deceptive policy is trained by hacking the environment and discovering a set of trajectories routing to the lowest reward or the worst-case performance. Next, the adversary misleads the victim to imitate the deceptive policy by perturbing the observations. Compared to existing approaches, it is theoretically shown that our adversary is strong under an appropriate noise level. Extensive experiments demonstrate the superiority of the proposed method in terms of efficiency and effectiveness, achieving state-of-the-art performance in both Atari and MuJoCo environments.

关键词： deep learning reinforcement learning adversarial robustness adversarial attack

Joint Optimization of Trajectory and Task Offloading for Cellular-Connected Multi-UAV Mobile Edge Computing

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Chinese Journal of Electronics 2024年第3期33卷 823-832页

作者： Jingming XIA Yufeng LIU Ling TAN School of Artificial Intelligence Nanjing University of Information Science and Technology Engineering research center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology

Since the computing capacity and battery energy of unmanned aerial vehicle(UAV) are constrained,UAV as aerial user is hard to handle the high computational complexity and time-sensitive *** paper investigates a cellular-connected multi-UAV network supported by mobile edge *** UAVs carrying tasks fly from a given initial position to a termination position within a specified *** handle the large number of tasks carried by UAVs,we propose a energy cost of all UAVs based problem to determine how many tasks should be offloaded to high-altitude balloons(HABs) for computing,where UAV-HAB association,the trajectory of UAV,and calculation task splitting are jointly ***,the formulated problem has nonconvex ***,an efficient iterative algorithm by applying successive convex approximation and the block coordinate descent methods is put ***,in each iteration,the UAV-HAB association,calculation task splitting,and UAV trajectory are alternately ***,for the nonconvex UAV trajectory optimization problem,an approximate convex optimization problem is *** numerical results indicate that the scheme of this paper proposed is guaranteed to converge and also significantly reduces the entire power consumption of all UAVs compared to the benchmark schemes.

关键词： Energy consumption Multi-access edge computing Costs Power demand Autonomous aerial vehicles Iterative algorithms Convex functions

WavEnhancer: Unifying Wavelet and Transformer for Image Enhancement

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Journal of Computer Science & technology 2024年第2期39卷 336-345页

作者：李梓诺陈绪行郭淑娜王书强潘治文 Department of Computer and information Science University of MacaoMacao 999078China research center for Biomedical information technology Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Image enhancement is a widely used technique in digital image processing that aims to improve image aesthetics and visual quality. However, traditional methods of enhancement based on pixel-level or global-level modifications have limited effectiveness. Recently, as learning-based techniques gain popularity, various studies are now focusing on utilizing networks for image enhancement. However, these techniques often fail to optimize image frequency domains. This study addresses this gap by introducing a transformer-based model for improving images in the wavelet domain. The proposed model refines various frequency bands of an image and prioritizes local details and high-level features. Consequently, the proposed technique produces superior enhancement results. The proposed model’s performance was assessed through comprehensive benchmark evaluations, and the results suggest it outperforms the state-of-the-art techniques.

关键词： transformer wavelet transform image enhancement

Resource Allocation for Channel Estimation in Reconfigurable Intelligent Surface-Aided Multi-Cell Networks

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Journal of Communications and information Networks 2024年第1期9卷 64-79页

作者： Yining Xu Sheng Zhou Department of Electronic Engineering Beijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China

Reconfigurable intelligent surface(RIS)is a promising solution to deal with the blockage-sensitivity of millimeter wave band and reduce the high energy consumption caused by network densification. However, deploying large scale RISs may not bring expected performance gain due to significant channel estimation overhead and non-negligible reflected *** this paper,we derive the analytical expressions of the coverage probability, area spectrum efficiency(ASE)and energy efficiency (EE)of a downlink RIS-aided multi-cell *** order to optimize the network performance, we investigate the conditions for the optimal number of training symbols of each antenna-to-antenna and antenna-to-element path (referred to as the optimal unit training overhead) in channel *** study shows that:1)RIS deployment is not“the more, the better”, only when blockage objects are dense should one deploy more RISs;2) the coverage probability is maximized when the unit training overhead is designed as large as possible;3)however,the ASE-and-EE-optimal unit training overhead exists. It is a monotonically increasing function of the frame length and a monotonically decreasing function of the average signal-to-noise-ratio (in the high signal-to-noise-ratio region). Additionally,the optimal unit training overhead is smaller when communication nodes deploy particularly few or many antennas.

关键词： reconfigurable intelligent surface multi-cell network directional transmissions channel estimation resource allocation stochastic geometry

Privacy-Preserving Federated Deep Learning Diagnostic Method for Multi-Stage Diseases

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3085-3099页

作者： Jinbo Yang Hai Huang Lailai Yin Jiaxing Qu Wanjuan Xie School of Computer Science and technology Harbin University of Science and TechnologyHarbin150080China Shanghai Futures information technology Co. Ltd.Shanghai201201China Heilongjiang Province Cyberspace research center Harbin150001China information Network Engineering and research center South China University of TechnologyGuangzhou510641China

Diagnosing multi-stage diseases typically requires doctors to consider multiple data sources,including clinical symptoms,physical signs,biochemical test results,imaging findings,pathological examination data,and even genetic *** applying machine learning modeling to predict and diagnose multi-stage diseases,several challenges need to be ***,the model needs to handle multimodal data,as the data used by doctors for diagnosis includes image data,natural language data,and structured ***,privacy of patients’data needs to be protected,as these data contain the most sensitive and private ***,considering the practicality of the model,the computational requirements should not be too *** address these challenges,this paper proposes a privacy-preserving federated deep learning diagnostic method for multi-stage *** method improves the forward and backward propagation processes of deep neural network modeling algorithms and introduces a homomorphic encryption step to design a federated modeling algorithm without the need for an *** also utilizes dedicated integrated circuits to implement the hardware Paillier algorithm,providing accelerated support for homomorphic encryption in ***,this paper designs and conducts experiments to evaluate the proposed *** experimental results show that in privacy-preserving federated deep learning diagnostic modeling,the method in this paper achieves the same modeling performance as ordinary modeling without privacy protection,and has higher modeling speed compared to similar algorithms.

关键词： Vertical federation homomorphic encryption deep neural network intelligent diagnosis machine learning and big data

Robust textile-based spoof plasmonic frequency scanning antenna for on-body IoT applications

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Science China(information Sciences) 2024年第8期67卷 269-284页

作者： Zhao-Min CHEN Jun-Lin ZHAN Hao CHEN Ya LI Hongjun HE Wu YANG Zhen-Guo LIU Wei-Bing LU State Key Lab of Millimeter Waves School of Information Science and EngineeringSoutheast University center for Flexible RF technology Frontiers Science Center for Mobile Information Communication and SecuritySoutheast University Future research Laboratory China Mobile Research Institute Purple Mountain Laboratories

Securing a comfortable, wearable compact frequency beam scanning antenna(FBSA) with robustness to deformation, low specific absorption rate(SAR), and good coverage of the surrounding environment for Internet of Things(IoT) applications, such as on-body navigation and wireless communication is an emerging challenge. In this work, a robust textile-based spoof plasmonic frequency scanning antenna utilizing higher-order modes is presented, which is also robust to deformation caused by the activities of the human body. The innovative design of the element ensures the high-efficiency transmission of the fundamental mode of spoof surface plasmon polaritons(SSPP) structure, providing the potential of being a multifunctional composite device in the compact on-body network. Besides, an artificial magnetic conductor(AMC) is designed underneath the SSPP structure, obtaining a low SAR value(0.113 W/kg), which ensures the safety of users. As a practical realization of this concept, a textile-based spoof plasmonic antenna was fabricated in the microwave regime and the performed experimental results show the proposed antenna has a single-beam radiation characteristic with a 70° beam scanning angle range when the frequency is 4.7–6.0 GHz with a high average realized gain of 13.15 dBi. And it still maintains a steady performance when faced with structure deformation, which proves its robustness. Wireless communication quality experiments are performed to demonstrate the proposed antenna can measure the angles of targets and realize wireless signal transmission to specific targets as the frequency varies, it may find great potential in the field of on-body IoT applications.

关键词： frequency beam scanning antenna (FBSA) Internet of Things (IoT) on-body communication spoof surface plasmon polaritons (SSPP) textile-based antenna