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Echo State network Based on Improved Knowledge Distillation for Edge Intelligence

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Chinese Journal of Electronics 2024年第1期33卷 101-111页

作者： Jian ZHOU Yuwen JIANG Lijie XU Lu ZHAO Fu XIAO College of Computer Nanjing University of Posts and Telecommunications Jiangsu High technology Research key laboratory for wireless sensor networks

Echo state network(ESN) as a novel artificial neural network has drawn much attention from time series prediction in edge intelligence. ESN is slightly insufficient in long-term memory, thereby impacting the prediction performance. It suffers from a higher computational overhead when deploying on edge devices. We firstly introduce the knowledge distillation into the reservoir structure optimization, and then propose the echo state network based on improved knowledge distillation(ESN-IKD) for edge intelligence to improve the prediction performance and reduce the computational overhead. The model of ESN-IKD is constructed with the classic ESN as a student network, the long and short-term memory network as a teacher network, and the ESN with double loop reservoir structure as an assistant network. The student network learns the long-term memory capability of the teacher network with the help of the assistant network. The training algorithm of ESN-IKD is proposed to correct the learning direction through the assistant network and eliminate the redundant knowledge through the iterative pruning. It can solve the problems of error learning and redundant learning in the traditional knowledge distillation process. Extensive experimental simulation shows that ESN-IKD has a good time series prediction performance in both long-term and short-term memory, and achieves a lower computational overhead.

关键词： Echo state network Reservoir structure optimization Knowledge distillation Edge intelligence Time series prediction

Gray code based gradient-free optimization algorithm for parameterized quantum circuit

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Chinese Physics B 2024年第2期33卷 189-194页

作者：张安琪武春辉赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China key laboratory of Broadband wireless Communication and sensor network technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China

A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this work.Each parameter of PQCs is encoded as a binary string,named as a gene,and a genetic-based method is adopted to select the offsprings.The individuals in the offspring are decoded in Gray code way to keep Hamming distance,and then are evaluated to obtain the best one with the lowest cost value in each iteration.The algorithm is performed iteratively for all parameters one by one until the cost value satisfies the stop condition or the number of iterations is reached.The GCO algorithm is demonstrated for classification tasks in Iris and MNIST datasets,and their performance are compared by those with the Bayesian optimization algorithm and binary code based optimization algorithm.The simulation results show that the GCO algorithm can reach high accuracies steadily for quantum classification tasks.Importantly,the GCO algorithm has a robust performance in the noise environment.

关键词： gradient-free optimization Gray code genetic-based method

Dual-Mode Resonant Sectorial Monopole Antenna with Stable Backfire Gain

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Chinese Journal of Electronics 2024年

作者： Feiyan JI Heng ZHANG Xiuqiong XING Wenjun LU Lei ZHU Jiangsu key laboratory of wireless communications Nanjing University of Posts and Telecommunications key laboratory of wireless sensor network & Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

A novel design approach to wideband, dual-mode resonant monopole antenna with stable, enhanced backfire gain is advanced. The sectorial monopole evolves from a linear, 0.75-wavelength electric prototype monopole under wideband dual-mode resonant operation. As theoretically predicted by the two resonant modes TE9/5,1and experimentally validated at 2.4-GHz band, the designed antenna exhibits a wide impedance bandwidth over 90.1%(i.e., 2.06-5.44 GHz), in which the stable gain bandwidth in the backfire,-x-direction(θ = 90°, φ = 180°) with peak value of 3.2 dBi and fluctuation less than 3 dB is up to 45.3%(i.e., 3.74-5.44 GHz). It is concluded that the stable wideband backfire gain frequency response should be owing to the high-order resonant mode in the unique sectorial monopole antennas.

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Power Allocation for SE Maximization in Uplink Massive MIMO System Under Minimum Rate Constraint

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China communications 2024年第3期21卷 104-117页

作者： Wang Hui Yu Xiangbin Liu Fuyuan Bai Jiawei College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China key laboratory of wireless sensor network and Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China

In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(MIMO)system with imperfect channel state information(CSI)over Rayleigh fading channel.The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user.Then,we develop a near-optimal power allocation(PA)scheme by using the successive convex approximation(SCA)method,Lagrange multiplier method,and block coordinate descent(BCD)method,and it can obtain almost the same SE as the benchmark scheme with lower complexity.Since this scheme needs three-layer iteration,a suboptimal PA scheme is developed to further reduce the complexity,where the characteristic of massive MIMO(i.e.,numerous receive antennas)is utilized for convex reformulation,and the rate constraint is converted to linear constraints.This suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal scheme.Finally,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint PA.Simulation results verify the effectiveness of the proposed schemes,and superior SE performance is achieved.

关键词： imperfect CSI massive MIMO minimum rate constraint power allocation spectral efficiency

Diffraction deep neural network-based classification for vector vortex beams

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Chinese Physics B 2024年第3期33卷 387-392页

作者：彭怡翔陈兵王乐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications (NJUPT)Nanjing 210003China key laboratory of Broadband wireless Communication and sensor network technology Ministry of EducationNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum communications.However,a VVB is unavoidably affected by atmospheric turbulence(AT)when it propagates through the free-space optical communication environment,which results in detection errors at the receiver.In this paper,we propose a VVB classification scheme to detect VVBs with continuously changing polarization states under AT,where a diffractive deep neural network(DDNN)is designed and trained to classify the intensity distribution of the input distorted VVBs,and the horizontal direction of polarization of the input distorted beam is adopted as the feature for the classification through the DDNN.The numerical simulations and experimental results demonstrate that the proposed scheme has high accuracy in classification tasks.The energy distribution percentage remains above 95%from weak to medium AT,and the classification accuracy can remain above 95%for various strengths of turbulence.It has a faster convergence and better accuracy than that based on a convolutional neural network.

关键词： vector vortex beam diffractive deep neural network classification atmospheric turbulence

Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

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Digital communications and networks 2024年第1期10卷 101-108页

作者： Haie Dou Lei Wang Bin Kang Baoyu Zheng key Lab of Broadband wireless Communication and sensor network technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing210003China School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

关键词： Orbital angular momentum Millimeter wave Off-axis misalignment Mode selection Capacity

QoE oriented intelligent online learning evaluation technology in B5G scenario

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Digital communications and networks 2024年第1期10卷 7-15页

作者： Mingzi Chen Xin Wei Peizhong Xie Zhe Zhang School of communications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China key Lab of Broadband wireless Communication and sensor network technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing210003China Institute of Higher Education Nanjing University of Posts and TelecommunicationsNanjing210003China

Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always satisfactory.The technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the users.Factors that affect the Quality of Online Learning Experience(OL-QoE)become more complicated.To get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology theory.Specifically,we first formulate a general definition of OL-QoE by data analysis and experimental verification.This formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect OLQoE.Then,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE prediction.Since the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation complexity.Finally,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE values.Through timely interventions,their OL-QoE and learning performance can be improved.Experimental results verify the effectiveness oftheproposed scheme.

关键词： B5G Online learning Quality of experience

Generation of orbital angular momentum hologram using a modified U-net

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Chinese Physics B 2024年第3期33卷 401-407页

作者：郑志刚韩菲菲王乐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China key laboratory of Broadband wireless Communication and sensor network technology (Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM)holography has become a promising technique in information encryption,data storage and opto-electronic computing,owing to the infinite topological charge of one single OAM mode and the orthogonality of different OAM modes.In this paper,we propose a novel OAM hologram generation method based on a densely connected U-net(DCU),where the densely connected convolution blocks(DCB)replace the convolution blocks of the U-net.Importantly,the reconstruction process of the OAM hologram is integrated into DCU as its output layer,so as to eliminate the requirement to prepare training data for the OAM hologram,which is required by conventional neural networks through an iterative algorithm.The experimental and simulation results show that the OAM hologram can rapidly be generated with the well-trained DCU,and the reconstructed image's quality from the generated OAM hologram is significantly improved in comparison with those from the Gerchberg-Saxton generation method,the Gerchberg-Saxton based generation method and the U-net method.In addition,a 10-bit OAM multiplexing hologram scheme is numerically demonstrated to have a high capacity with OAM hologram.

关键词： orbital angular momentum(OAM) holography OAM holography deep learning

Improved decoy-state quantum key distribution with uncharacterized heralded single-photon sources

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Chinese Physics B 2024年第2期33卷 204-208页

作者：徐乐辰张春辉周星宇王琴 Institute of Quantum Information and technology Nanjing 210003China Broadband wireless Communication and sensor network technology Key Laboratory of Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China Telecommunication and networks National Engineering Research Center Nanjing University of Posts and TelecommunicationsNanjing 210003China

Encoding system plays a significant role in quantum key distribution(QKD).However,the security and performance of QKD systems can be compromised by encoding misalignment due to the inevitable defects in realistic devices.To alleviate the influence of misalignments,a method exploiting statistics from mismatched basis is proposed to enable uncharacterized sources to generate secure keys in QKD.In this work,we propose a scheme on four-intensity decoy-state quantum key distribution with uncharacterized heralded single-photon sources.It only requires the source states are prepared in a two-dimensional Hilbert space,and can thus reduce the complexity of practical realizations.Moreover,we carry out corresponding numerical simulations and demonstrate that our present four-intensity decoy-state scheme can achieve a much higher key rate compared than a three-intensity decoy-state method,and meantime it can obtain a longer transmission distance compared than the one using weak coherent sources.

关键词： quantum key distribution heralded single-photon source decoy-state method