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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Wang, Sifan Zhu, Qiangqiang Wu, Yang Hu, Zhiming Xu, Ruofeng Zhao, Lei China University of Mining and Technology School of Information and Control Engineering Xuzhou China

ISBN: (纸本)9798350355581

This paper proposed the Discontinuous Galerkin Time-Domain (DGTD) methods for simulating a bidirectional PIN limiter using the Modified Nodal Analysis-Simulation Program with Integrated Circuit Emphasis (MNA-SPICE). The proposed method combines the advantages of MNA-SPICE for circuit simulation with the high accuracy and efficiency of DGTD for electromagnetic field analysis. Numerical simulations demonstrate the effectiveness and reliability of this method. © 2024 IEEE.

关键词： Time domain analysis

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Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

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Digital communications and Networks 2024年第1期10卷 53-62页

作者： Zhipeng Cheng Minghui Liwang Ning Chen Lianfen Huang Nadra Guizani Xiaojiang Du Department of Information and Communication Engineering Xiamen UniversityXiamen361005China School of Electrical and Computer Engineering University of Texas at ArlingtonArlingtonTX76019USA Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ07030USA

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in ***,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective *** this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground *** goal was to mitigate co-channel interference while maximizing long-term system *** problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this *** simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

关键词： UAV-user association Multi-connectivity Resource allocation Power control Multi-agent deep reinforcement learning

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Traveling wave fault location in distribution networks based on SSA-VMD 4

Traveling wave fault location in distribution networks based...

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4th IEEE International Conference on Electronic technology, communication and information, ICETCI 2024

作者： Sun, Jingyang Pang, Qingle Zhou, Tai Qingdao University of Technology School of Information and Control Engineering Qingdao266520 China

ISBN: (纸本)9798350361643

In response to the issue of the empirical dependence of penalty parameter α and mode number K in the fault distance measurement accuracy for the variational mode decomposition-based fault location method, a distribution network traveling wave fault location method is proposed. This method optimizes the variational mode decomposition (VMD) using Sparrow Search Algorithm (SSA). By applying SSA to optimize VMD parameters, the optimal parameter combination [K,α] is obtained. Subsequently, using the optimized VMD parameters, the collected fault current traveling wave signals from the line are processed to determine the fault location, completing the fault distance measurement. The proposed fault location method is validated using transient simulation software ATP on a 10 kV distribution network system. The results indicate that this research method can rapidly and accurately determine the fault location, enhancing the reliability of traveling wave protection and fault distance measurement. © 2024 IEEE.

关键词： Variational mode decomposition

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Cross-Attention Dual-Stream Fusion for Speech Emotion Recognition

Cross-Attention Dual-Stream Fusion for Speech Emotion Recogn...

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2024 IEEE Pacific Rim Conference on communications, Computers and Signal Processing, PACRIM 2024

作者： Yu, Shaode Meng, Jiajian Zhu, Bing Sun, Qiurui School of Information and Communication Engineering Communication University of China Beijing China Beijing Normal University Center of Information & Network Technology Beijing China

ISBN: (纸本)9798350362312

Speech emotion recognition aims for recognizing human subjective emotions through in-depth audio signal analysis. It benefits a wide range of downstream applications and tasks. However, how to comprehensively encode emotion cues and how to effectively fuse implicit information still remains challenging. To address the issues, dual-stream representation is designed that uses full-training of TextRCNN from log-Mel spectrograms and fine-tuning of pre-trained HuBERT from raw audio signals for emotion encoding, and cross-attention fusion (CAF) is developed for valid integration of dual-stream outputs. On the IEMOCAP of four emotions ('happy+excited', 'sad', 'angry', and 'neutral'), the effectiveness of the framework is evaluated by using different dual-stream encoders (DPCNN and pre-trained Wave2Vec2) and different fusion modules (summation, concatenation, feature-wise linear modulation, and CAF). Experimental results reveal that the proposed framework achieves promising performance (weighted accuracy, 0.6965;unweighted accuracy, 0.7088;F1-score, 0.7084), the dual-stream encoder enriches emotion representation, and the CAF outperforms the other three modules. For further improving the performance, multi-stream representation and multi-branch feature fusion would be the research direction. Our code will be available on GitHub (https://***/NicoYuCN/serCAF). © 2024 IEEE.

关键词： Emotion Recognition

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Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter communication System

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China communications 2024年第2期21卷 197-209页

作者： Peizhong Xie Junjie Jiang Ting Li Yin Lu School of Communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing 210003China

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization *** iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

关键词： energy efficiency joint optimization UAV-assisted backscatter communication user trajectory

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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 595-607页

作者： Jianguo Zhao Chunyu Yang Weinan Gao Linna Zhou Xiaomin Liu the Engineering Research Center of Intelligent Control for Underground Space Ministry of EducationChina University of Mining and TechnologyXuzhou 221116 the School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116 IEEE the State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation *** the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost *** the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement *** combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop *** proposed decomposition design not only bypasses the numerical stiffness but also alleviates the *** efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

关键词： Adaptive optimal control decentralized control output regulation reinforcement learning(RL) singularly perturbed systems(SPSs)

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An Improved Convolutional Neural Network Based Indoor Localization by Using Jenks Natural Breaks Algorithm

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China communications 2022年第4期19卷 291-301页

作者： Chengjie Hou Yaqin Xie Zhizhong Zhang School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqingChina School of Electronic and Information Engineering Nanjing University of Information Science and TechnologyNanjingChina

With the rapid growth of the demand for indoor location-based services(LBS), Wi-Fi received signal strength(RSS) fingerprints database has attracted significant attention because it is easy to obtain. The fingerprints algorithm based on convolution neural network(CNN) is often used to improve indoor localization accuracy. However, the number of reference points used for position estimation has significant effects on the positioning accuracy. Meanwhile, it is always selected arbitraily without any guiding standards. As a result, a novel location estimation method based on Jenks natural breaks algorithm(JNBA), which can adaptively choose more reasonable reference points, is proposed in this paper. The output of CNN is processed by JNBA, which can select the number of reference points according to different environments. Then, the location is estimated by weighted K-nearest neighbors(WKNN). Experimental results show that the proposed method has higher positioning accuracy without sacrificing more time cost than the existing indoor localization methods based on CNN.

关键词： indoor localization convolution neural network(CNN) Wi-Fi fingerprints Jenks natural breaks

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Combustion characteristics of millimeter-sized aluminum particles in fluidized bed under various O_(2)/CO_(2)/H_(2)O atmospheres Author links open overlay panel

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Particuology 2024年第8期91卷 315-322页

作者： Jialing Zhou Rui Zhang Dong Liu Key Laboratory of Thermal Control of Electronic Equipment Ministry of Industry and Information TechnologyNanjing210094China Advanced Combustion Laboratory School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing210094China

Aluminum is an attractive alternative fuel,but it burns very inefficiently due to the formation of a dense Al_(2)O_(3)layer which prevents O_(2)from diffusion to the surface of Al *** previous experiments,the combustion of millimeter-sized Al(mAl)particles in the fluidized bed has achieved a substantial increase in the combustion efficiency,but further improvements are still *** this study,the effects of reaction atmosphere on the fluidized combustion of mAl particles were *** experiments with different O_(2)/H_(2)O/CO_(2)concentrations were *** experimental results indicate that the combustion efficiency of mAl particles in fluidized bed increases as the mole fraction of O_(2),H_(2)O or CO_(2)increases,and the highest combustion efficiency can reach 38.7%.After the analysis of the oxide film on the surface of aluminum particles,it was found that it is easier to generate the unstableθ-Al_(2)O_(3)under CO_(2)atmosphere,and it is easier to generate the unstableγ-Al_(2)O_(3)andθ-Al_(2)O_(3)under H_(2)O *** unstable Al_(2)O_(3)film is more likely to be abraded in the fluidized bed,which leads to the effective improvement of the combustion efficiency.

关键词： Al combustion Fluidized bed Atmosphere Combustion efficiency

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Coordinated Deception Jamming Power Scheduling for Multijammer Systems Against Distributed Radar Systems

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 1076-1088页

作者： Sun, Jun Yuan, Ye Sabrina Greco, Maria Gini, Fulvio University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China University of Pisa Information Engi-neering Pisa56126 Italy

The rapid development of cooperative techniques and anti-jamming methods in modern radar systems has significantly improved the mission performance and survivability of radars. In practical applications, the single jammer system cannot cope with the cooperative technology of the radar system due to its single interference pattern and spatial angle. To combat distributed radar systems, in this article, we construct and solve a resource management problem with the goal of minimizing the false target rejection probability, while being constrained by the deception jamming power budget of the multijammer system. First, the posterior Cramér-Rao lower bounds (PCRLBs) including target state and deception parameters related to the radar system under deception jamming are derived. On this basis, a false target discriminator is designed and the corresponding rejection probability is derived, which is regarded as the metric to assess the deception jamming performance. Then, the deception jamming power scheduling (DJPS) problem of the multijammer system for cooperatively combating distributed radar systems is constructed, subject to the system resource configurations. Due to the nonconvexity of the false target rejection probability, the formulated problem is inherently nonconvex. To effectively address this problem, a modified particle swarm optimization (MPSO) algorithm is presented. Numerical simulations verify that the proposed strategy and MPSO algorithm show superior deception jamming performance in combating distributed radar systems. © 2023 IEEE.

关键词： Cramer-Rao bounds

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Energy Efficiency Maximization for Cooperative NOMA with Hardware Impairments

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China communications 2024年第12期21卷 80-91页

作者： Wang Zhengqiang Chang Ruifei Wan Xiaoyu Fan Zifu Duo Bin School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer Science and Cyber Security Chengdu University of TechnologyChengdu 610059China

The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)***,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the *** original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution ***,we use fractional programming to convert the EE maximization problem as a series of subtraction form ***,variable substitution and block coordinate descent(BCD)method are used to handle the ***,a resource allocation algorithm is proposed to maximize the EE of the ***,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.

关键词： block coordinate descent cooperative non-orthogonal multiple access energy efficiency hardware impairments resource allocation

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