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A Graph-Based Semi-Supervised Approach for Few-Shot Class-Incremental Modulation Classification

China communications 2024年第11期21卷 88-103页

作者： Zhou Xiaoyu Qi Peihan Liu Qi Ding Yuanlei Zheng Shilian Li Zan State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China The No.011 Research Center Science and Technology on Communication Information Security Control LaboratoryJiaxing 314033China

With the successive application of deep learning(DL)in classification tasks,the DL-based modulation classification method has become the preference for its state-of-the-art ***,once the DL recognition model is pre-trained with fixed classes,the pre-trained model tends to predict incorrect results when identifying incremental ***,the incremental classes are usually emergent without lab.l information or only a few lab.led samples of incremental classes can be *** this context,we propose a graphbased semi-supervised approach to address the fewshot classes-incremental(FSCI)modulation classification *** proposed method is a twostage learning method,specifically,a warm-up model is trained for classifying old classes and incremental classes,where the unlab.led samples of incremental classes are uniformly lab.led with the same lab.l to alleviate the damage of the class imbalance *** the warm-up model is regarded as a feature extractor for constructing a similar graph to connect lab.led samples and unlab.led samples,and the lab.l propagation algorithm is adopted to propagate the lab.l information from lab.led nodes to unlab.led nodes in the graph to achieve the purpose of incremental classes *** results prove that the proposed method is superior to other finetuning methods and retrain methods.

关键词： deep learning few-shot lab.l propagation modulation classification semi-supervised learning

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A Flexible Multifunctional Absorber/Reflector with Wideband and Low Power Performance

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IEEE Antennas and Wireless Propagation Letters 2025年第6期24卷 1552-1556页

作者： Liang, Xinhua Chen, Zhao-Min Zhu, Lin Cao, Qunsheng Nanjing University of Aeronautics and Astronautics Department of Electronic and Information Engineering Nanjing211106 China Southeast University State Key Lab of Millimeter Waves School of Information Science and Engineering Center for Flexible RF Technology Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

This paper presents a multifunctional flexible absorber/reflector with wideband performance and low power consumption. The proposed unit cell utilizes only two PIN diodes to achieve four distinct functions with low power consumption. By integrating the metal structure of the unit cell with the PIN diode bias lines, the design is simplified. In addition, the physical characteristics of the proposed structure are thoroughly analyzed using equivalent circuit theory, electric field analysis, and surface current distribution, enhancing the understanding of the design mechanisms. The simulation and experimental verification results are in agreement. Four distinct functions are successfully demonstrated within the frequency band of 8.5 GHz - 12.5 GHz, with a maximum power consumption of only 0.078 W. © 2002-2011 IEEE.

关键词： PIN diodes

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Energy Minimization Oriented Resource Allocation for Relay Assisted NOMA-MEC Networks

Energy Minimization Oriented Resource Allocation for Relay A...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Wang, Qianru Qian, Liping Wu, Yuan Yang, Xiaoniu Zhejiang University of Technology College of Information Engineering Hangzhou China University of Macau State Key Laboratory of Internet of Things for Smart City China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Zhejiang University of Technology Institute of Cyberspace Security Hangzhou310023 China

ISBN: (纸本)9798350351255

With the growing demand for image transmission, there is a need for solutions that offer low energy consumption and low latency. In this paper, we present a novel relay-assisted system based on non-orthogonal multiple access (NOMA) and mobile edge computing (MEC). Our proposed system compresses images at the device end, decompresses them at either a relay or a cloud server (CS). The primary objective is to minimize system energy consumption under given task delay constraints. Considering that this is a non-convex optimization problem, we solve it by decomposing it into a continuous subproblem and a discrete subproblem. To solve the continuous subproblem, we convexify it by introducing new parameters and change variables to get the optimal the computing power of devices, relay and CS, sampling rate of devices, transmission power of devices and relay. To solve the discrete subproblem, we propose a cross-entropy (CE) algorithm to obtain the optimal decompression decision and subcarrier allocation decision. Simulation results demonstrate the accuracy and effectiveness of our algorithm in optimizing total energy consumption compared to the Linear Interactive and General Optimizer (LINGO) and frequency division multiple access (FDMA) methods. © 2024 IEEE.

关键词： Convex optimization

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Multi-scale network for single image deblurring based on ensemble learning module

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Multimedia Tools and Applications 2025年第11期84卷 9045-9064页

作者： Wu, WenBo Pan, Yun Su, Na Wang, JingTao Wu, ShaoChuan Xu, ZeKun Yu, YouJian Liu, YaPeng State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China School of Computer and Cyberspace Security Communication University of China Beijing100024 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China School of Computer and Information Engineering Tianjin Chengjian University Tianjin300384 China School of Computer Science and Technology Anhui University Hefei230601 China

In this paper, we have identified two primary issues with current multi-scale image deblurring methods. On the one hand, the blurring scale is ignored. On the other hand, the context information of images is not fully utilized, and the spatial detail information of images is lost. To better solve the above problems, on top of that, this paper proposes a multi-scale network for single image deblurring. The designed network contains two parts: 1) Ensemble Learning Model: The Weak Learning Model in this module connects multiple weak learners in series to increase network depth. Moreover, through multi-scale feature ensemble module, the output features and intermediate features of different weak learner are integrated, and finally strong learner is used to enhance the features with semantic information at different scales;2) Spatial Feature Enhancement Module: This module can preserve spatial detail information of images and compensate for the disadvantages of losing image spatial details due to continuous downsampling in the Ensemble Learning Model structure. Our proposed deblurring model has been extensively evaluated on several benchmark datasets, and the model achieves superior performance compared to the most advanced deblurring methods. In particular, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values are 33.57 dB and 0.965 on the GoPro dataset, respectively, with PSNR and SSIM improving by 0.49 dB and 0.002 over NAFNet, and 0.65 dB and 0.004 over Restormer. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Learning systems

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General Simultaneous Localization and Mapping Scheme for mmWave communication Systems

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IEEE Internet of Things Journal 2024年第12期11卷 22521-22536页

作者： Du, Tao Yang, Jie Wen, Chao-Kai Xia, Shuqiang Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory Of Measurement And Control Of Complex Systems Of Engineering Ministry Of Education The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China Institute Of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation The State Key Laboratory Of Mobile Network And Mobile Multimedia Technology Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China

Utilizing high-resolution antenna arrays and wide bandwidth of the millimeter-wave (mmWave) spectrum in 5G new radio (NR) mmWave communication systems holds the potential for high-throughput data transmission while enabling user localization and environmental mapping. However, the majority of existing simultaneous localization and mapping (SLAM) algorithms rely on methods akin to the extended Kalman filter for generating initial map features. These methods prove ineffective when the measurement dimension is insufficient. Furthermore, there is a notable absence of research exploring mmWave prototype systems to evaluate and compare the performance and viability of various SLAM algorithms. To address these challenges, we propose an innovative probability hypothesis density (PHD) generation scheme for birth events and have developed a prototype system. Our approach, referred to as PHD-SLAM, exhibits remarkable effectiveness even in scenarios where the measurement dimension falls short of map features. This means it can function seamlessly with only delay or angle information availab.e. Additionally, we have designed a 28GHz mmWave beam scanning prototype system that leverages the 5G NR frame for accomplishing SLAM algorithms. Following this, we conducted extensive simulations and experimental evaluations to gauge the performance of several leading-edge SLAM algorithms under diverse mmWave circumstances, encompassing PHD-based and belief propagation (BP) SLAM algorithms. Our analysis reveals that both PHD and BP SLAM can achieve agent localization precision within a decimeter and mapping precision within a meter, capitalizing on the angle parameters of mmWave signals. While BP SLAM showcases reduced computational demand, its estimation precision is marginally inferior to that of PHD-SLAM. © 2014 IEEE.

关键词： Belief propagation

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Efficient Artificial Neural Networks Model for the Layout of Platform-based dual-Antennas Mutual Coupled 15

Efficient Artificial Neural Networks Model for the Layout of...

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15th International Conference on Microwave and Millimeter Wave technology, ICMMT 2023

作者： Weng, Rui Sun, Dingyi Yang, Wu Lu, Weibing Southeast University Center for Flexible Rf Technology State Key Lab of Millimeter Waves School of Information Science and Engineering Nanjing210096 China Purple Mountain Laboratories Moe Frontiers Science for Mobile Information Communication and Security Nanjing210096 China

ISBN: (纸本)9798350338874

To expedite the design process of the platform-based dual-antenna mutually coupled layout, the inverse artificial neural networks(ANNs) model is proposed, which can directly generate the layout to match the expected electromagnetic response. In this ANNs model, the two antenna coupling performance S-parameter is regarded as the input, and the corresponding discrete points are the output. Once the training is completed, the proposed inverse model can provide the corresponding antennas located point directly without an optimization process. In the last, two examples are presented to demonstrate the accuracy and efficiency of the proposed method. © 2023 IEEE.

关键词： Neural networks

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Two-Step Adaptive Anti-Mainlobe-Jamming Processing for Polarimetric Conformal Arrays

Two-Step Adaptive Anti-Mainlobe-Jamming Processing for Polar...

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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Wanpeng Huang Jinyang He Ziyang Cheng Zishu He Sch. of Information & Communication Eng. University of Electronic Science and Technology of China Guangdong Key Lab. of Intelligent Information Processing & Shenzhen Key Lab. of Media Security

Mainlobe jamming will cause a serious performance loss for conventional arrays with minimum variance distortionless response (MVDR) beamforming. The polarization-space processing is an effective way to suppress it. However, because of increasing an additional dimension, more training samples are required in estimating the sample covariance matrix. In this paper, we investigate the problem of anti-mainlobe-jamming for polarimetric conformal arrays. In order to overcome the above challenge, a Two-step Adaptive Processing method is proposed. Specifically, in the first step, training samples are overlapping and used to achieve the MVDR beamformers. Then, in the second step, the polarization-space filter is processed the MVDR outputs based on solving the constrained jamming power minimization problem. Finally, numerical simulations demonstrate the superiority of the proposed method over the conventional MVDR method.

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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

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Distributionally robust optimization based chance-constrained energy management for hybrid energy powered cellular networks

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Digital communications and Networks 2023年第3期9卷 797-808页

作者： Pengfei Du Hongjiang Lei Imran Shafique Ansari Jianbo Du Xiaoli Chu The Engineering Research Center of Intelligent Air-ground Integrated Vehicle and Traffic Control Ministry of EducationXihua UniversityChengdu610039China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an710121China Electronic and Electrical Engineering University of SheffieldSheffieldS102TNUK

Energy harvesting has been recognized as a promising technique with which to effectively reduce carbon emis-sions and electricity expenses of base ***,renewable energy is inherently stochastic and inter-mittent,imposing formidable challenges on reliably satisfying users'time-varying wireless traffic *** addition,the probability distribution of the renewable energy or users’wireless traffic demand is not always fully known in *** this paper,we minimize the total energy cost of a hybrid-energy-powered cellular network by jointly optimizing the energy sharing among base stations,the battery charging and discharging rates,and the energy purchased from the grid under the constraint of a limited battery size at each base *** solving the formulated non-convex chance-constrained stochastic optimization problem,a new ambiguity set is built to characterize the uncertainties in the renewable energy and wireless traffic demands according to interval sets of the mean and *** this ambiguity set,the original optimization problem is transformed into a more tractable second-order cone programming problem by exploiting the distributionally robust optimization ***,a low-complexity distributionally robust chance-constrained energy management algo-rithm,which requires only interval sets of the mean and covariance of stochastic parameters,is *** results of extensive simulation are presented to demonstrate that the proposed algorithm outperforms existing methods in terms of the computational complexity,energy cost,and reliability.

关键词： Cellular networks Energy harvesting Energy management Chance-constrained Distributionally robust optimization

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Zhao, Yihan Duan, Xuting Zhou, Jianshan Zhang, Long School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9798350316308

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time. © 2023 IEEE.

关键词： Autonomous vehicles

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