Online First

Online First Papers are peer-reviewed and accepted for publication. Note that the papers under this directory, they are posted online prior to technical editing and author proofing. Please use with caution.
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IMAGE AND SIGNAL PROCESSING
Convolution theorem associated with the QWFRFT
MEI Yinyin, FENG Qiang, GAO Xiuxiu, ZHAO Yanbo
, Available online  , doi: 10.23919/cje.2021.00.225
Abstract(243) HTML (126) PDF(33)
Abstract:
The quaternion windowed fractional Fourier transform (QWFRFT) is a generalized form of the quaternion fractional Fourier transform (QFRFT), it plays a crucial role in signal processing for the analysis of multidimensional signals. In the first part of this paper, we give the definition of the two-sided QWFRFT and some fundamental properties. Secondly, the quaternion convolution is proposed, the relation between the quaternion convolution and the classical convolution is also given. Based on the quaternion convolution of the QWFRFT, relevant convolution theorems for the QWFRFT are studied. Thirdly, the fast algorithm for QWFRFT is discussed. The complexity of QWFRFT and the quaternion windowed fractional convolution are given.
Necessary Condition for the Success of Synchronous GNSS Spoofing
WANG Yiwei, KOU Yanhong, HUANG Zhigang
, Available online  , doi: 10.23919/cje.2021.00.307
Abstract(111) HTML (55) PDF(13)
Abstract:
A synchronous GNSS generator spoofer aims at directly taking over the tracking loops of the receiver with the lowest possible spoofing to signal ratio (SSR) without forcing it to lose lock. This paper investigates the factors that affect spoofing success and their relationships. The necessary conditions for successful spoofing are obtained by deriving the code tracking error in the presence of spoofing and analyzing the effects of SSR, spoofing synchronization errors, and receiver settings on the S-curve ambiguity and code tracking trajectory. The minimum SSRs for a successful spoofing calculated from the theoretical formulation agree with Monte Carlo simulations at digital intermediate frequency signal level within 1 dB when the spoofer pulls the code phase in the same direction as the code phase synchronization error, and the required SSRs can be much lower when pulling in the opposite direction. The maximum spoofing code phase error for a successful spoofing is tested by using TEXBAT datasets, which coincides with the theoretical results within 0.1 chip. This study reveals the mechanism of covert spoofing and can play a constructive role in the future development of spoofing and anti-spoofing methods.
Track-oriented Marginal Poisson Multi-Bernoulli Mixture Filter for Extended Target Tracking
DU Haocui, XIE Weixin, LIU Zongxiang, LI Liangqun
, Available online  , doi: 10.23919/cje.2021.00.194
Abstract(184) HTML (96) PDF(19)
Abstract:

In this paper, we derive and propose a track-oriented marginal Poisson multi-Bernoulli mixture (TO-MPMBM) filter to address the problem that the standard random finite set (RFS) filters cannot build continuous trajectories for multiple extended targets. Firstly, the Poisson point process (PPP) model and the multi-Bernoulli mixture (MBM) model are used to establish the set of birth trajectories and the set of existing trajectories, respectively. Secondly, the proposed filter recursively propagates the marginal association distributions and the Poisson multi-Bernoulli mixture (PMBM) density over the set of alive trajectories. Finally, after pruning and merging process, the trajectories with existence probability greater than the given threshold are extracted as the estimated target trajectories. A comparison of the proposed filter with the existing trajectory filters in two classical scenarios confirms the validity and reliability of the TO-MPMBM filter.

A Low Complexity Distributed Multitarget Detection and Tracking Algorithm
FAN Jiande, XIE Weixin, LIU Zongxiang
, Available online  , doi: 10.23919/cje.2021.00.282
Abstract(341) HTML (162) PDF(35)
Abstract:

In this paper, we propose a low complexity distributed approach to address the multitarget detection/tracking problem in the presence of noisy and missing data. The proposed approach consists of two components: a distributed flooding scheme for measurements exchanging among sensors and a sampling-based clustering approach for target detection/tracking from the aggregated measurements. The main advantage of the proposed approach over the prevailing Markov-Bayes-based distributed filters is that it does not require any priori information and all the information required is the measurement set from multiple sensors. A comparison of the proposed approach with the available distributed clustering approaches and the cutting edge distributed multi-Bernoulli filters that are modeled with appropriate parameters confirms the effectiveness and the reliability of the proposed approach.

CIRCUITS & SYSTEMS
Modeling and Measurement of 3D Solenoid Inductor Based on Through-Silicon Vias
YIN Xiangkun, WANG Fengjuan, ZHU Zhangming, Vasilis F. Pavlidis, LIU Xiaoxian, LU Qijun, LIU Yang, YANG Yintang
, Available online  , doi: 10.23919/cje.2020.00.340
Abstract(109) HTML (54) PDF(14)
Abstract:
Through-silicon via (TSV) provides vertical interconnectivity among the stacked dies in three-dimensional integrated circuits (3D ICs) and is a promising option to minimize 3D solenoid inductors for on-chip radio-frequency applications. In this paper, a rigorous analytical inductance model of 3D solenoid inductor is proposed based on the concept of loop and partial inductance. And a series of 3D samples are fabricated on 12-in high-resistivity silicon wafer using low-cost standard CMOS-compatible process. The results of the proposed model match very well with those obtained by simulation and measurement. With this model, the inductance can be estimated accurately and efficiently over a wide range of inductor windings, TSV height, space, and pitch.
On-Chip Reconfigurable Microwave Photonic Processor
ZHANG Weifeng, WANG Bin
, Available online  , doi: 10.23919/cje.2020.00.273
Abstract(6) HTML (3) PDF(0)
Abstract:
Microwave photonic processors leverage the modern photonics technique to process the microwave signal in the optical domain, featuring high speed and broad bandwidth. Based on discrete optical and microwave components, different microwave photonic processors are reported. Due to the limitation of the opto-electronic components, most of the realized processors are designed to serve a specific demand. With the booming development of photonic integrated circuits (PICs), new possibilities are opened for the implementation of integrated microwave photonic processors. By using the high-precision planar fabrication process, on-chip microwave photonic processors are enabled to have unprecedently full reconfigurability to perform multiple processing tasks. An overview regarding our recent work on reconfigurable microwave photonic processors is presented with an emphasis on silicon photonics integrated solutions.
An Improved Path Delay Variability Model via Multi-Level Fan-Out-of-4 Metric for Wide-Voltage-Range Digital CMOS Circuits
CUI Yuqiang, SHAN Weiwei, DAI Wentao, LIU Xinning, GUO Jingjing, CAO Peng
, Available online  , doi: 10.23919/cje.2021.00.447
Abstract(158) HTML (83) PDF(16)
Abstract:
In advanced CMOS technology, process, voltage, and temperature (PVT) variations increase the paths’ latency in digital circuits, especially when operating at a low supply voltage. The fan-out-of-4 inverter chain (FO4 chain) metric has been proven to be a good metric to estimate the path’s delay variability, whereas the previous work ignored the non-independent characteristic between the adjacent cells in a path. In this study, an improved model of path delay variability is established to describe the relationship between the paths’ max-delay variability and an FO4 chain, which is based on multilevel FO4 metric and circuit-level parameters knobs (i.e., cell topology and driving strength) of the first few cells. We take the slew and load into account to improve the accuracy of this framework. Examples of 28 nm and 40 nm digital circuits show that our model conforms with Monte Carlo simulations as well as fabricated chips’ measurements. It is able to model the delay variability effectively to speed up the design process with limited accuracy loss. It also provides a deeper understanding and quick estimation of the path delay variability from the near-threshold to nominal voltages.
Analysis of Capacitance Characteristics of Light-Controlled Electrostatic Conversion Device
LIU Yujie, WANG Yang, JIN Xiangliang, PENG Yan, LUO Jun, YANG Jun
, Available online  , doi: 10.23919/cje.2021.00.272
Abstract(81) HTML (40) PDF(14)
Abstract:
In recent years, converting environmental energy into electrical energy to meet the needs of modern society for clean and sustainable energy has become a research hotspot. Electrostatic energy is a pollution-free environmental energy source. The use of electrostatic conversion devices to convert electrostatic energy into electrical energy has been proven to be a feasible solution to meet sustainable development. This paper proposes a light-controlled electrostatic conversion device (LCECD). When static electricity comes, an avalanche breakdown occurs inside the LCECD and a low resistance path is generated to clamp the voltage, thereby outputting a smooth square wave of voltage and current. Experiments have proved that LCECD can convert 30kV electrostatic pulses into usable electrical energy for the normal operation of the back-end LED lights. In addition, the LCECD will change the parasitic capacitance after being exposed to light. For different wavelengths of light, the parasitic capacitance exhibited by the device will also be different. The smaller the parasitic capacitance of the LCECD, the higher the efficiency of its electrostatic conversion. This is of great significance to the design of electrostatic conversion devices in the future.
INFORMATION SECURITY AND CRYPTOLOGY
A Semi-shared Hierarchical Joint Model for Sequence Labeling
LIU Gongshen, DU Wei, ZHOU Jie, LI Jing, CHENG Jie
, Available online  , doi: 10.23919/cje.2020.00.363
Abstract(172) HTML (83) PDF(11)
Abstract:
Multi-task learning is an essential yet practical mechanism for improving overall performance in various machine learning fields. Owing to the linguistic hierarchy, the hierarchical joint model is a common architecture used in natural language processing. However, in the state-of-the-art hierarchical joint models, higher-level tasks only share bottom layers or latent representations with lower-level tasks thus ignoring correlations between tasks at different levels, i.e., lower-level tasks cannot be instructed by the higher features. This paper investigates how to advance the correlations among various tasks supervised at different layers in an end-to-end hierarchical joint learning model. We propose a semi-shared hierarchical model that contains cross-layer shared modules and layer-specific modules. To fully leverage the mutual information between various tasks at different levels, we design four different dataflows of latent representations between the shared and layer-specific modules. Extensive experiments on CTB-7 and CONLL-2009 show that our semi-shared approach outperforms basic hierarchical joint models on sequence tagging while having much fewer parameters. It inspires us that the proper implementation of the cross-layer sharing mechanism and residual shortcuts is promising to improve the performance of hierarchical joint natural language processing models while reducing the model complexity.
Code-Based Conjunction Obfuscation
ZHANG Zheng, ZHANG Zhuoran, ZHANG Fangguo
, Available online  , doi: 10.23919/cje.2020.00.377
Abstract(113) HTML (57) PDF(7)
Abstract:
A conjunction can be viewed as a pattern-matching with wildcards. An input string of length n matches a pattern of the same length if and only if it is same as the pattern for all non-wildcard positions. Since 2013, there are abundant works of conjunction obfuscations which are based on generic group model, learning with errors (LWE) assumption, learning parity with noise (LPN) assumption, etc. After obfuscation, any adversary can not find the pattern or a accepting input from the obfuscated program. In this work, we propose a conjunction obfuscation from the general decoding problem. In addition to satisfying the distributional virtual black-box security, our obfuscation also achieve the strong functionality preservation which solves the open problem in the work of Bartusek et al. in EUROCRYPT 2019. It means that we construct a conjunction obfuscation with simultaneous correct from a standard assumption. The conjunction obfuscation can resist the information set decoding attack and the structured error attack with some parameter constraints.
A Combined Countermeasure Against Side-Channel and Fault Attack with Threshold Implementation Technique
JIAO Zhipeng, CHEN Hua, FENG Jingyi, KUANG Xiaoyun, YANG Yiwei, LI Haoyuan, FAN Limin
, Available online  , doi: 10.23919/cje.2021.00.089
Abstract(330) HTML (146) PDF(39)
Abstract:
Side-channel attack (SCA) and fault attack (FA) are two classical physical attacks against cryptographic implementation. In order to resist them, we present a combined countermeasure scheme which can resist both SCA and FA. The scheme combines the threshold implementation and duplication-based exchange technique. The exchange technique can confuse the fault propagation path and randomize the faulty values. The threshold implementation technique can ensure a provable security against SCA. Moreover, it can also help to resist the FA by its incomplete property and random numbers. Compared with other methods, the proposed scheme has simple structure, which can be easily implemented in hardware and result in a low implementation cost. Finally, we present a detailed design for the block cipher light encryption device and implement it. The hardware cost evaluation shows our scheme has the minimum overhead factor.
Cryptanalysis of Full-Round Magpie Block Cipher
YANG Yunxiao, SUN Bing, LIU Guoqiang
, Available online  , doi: 10.23919/cje.2021.00.209
Abstract(183) HTML (82) PDF(20)
Abstract:
${\textsf{Magpie}}$ is a lightweight block cipher proposed by Li et al. at Acta Electronica Sinica 2017. It adopts an SPN structure with a block size of 64 bits and the key size of 96 bits, respectively. To achieve the consistency of the encryption and decryption, which is both hardware and software friendly, 16 bits of the key are used as control signals to select S-boxes and another 16 bits of the key are used to determine the order of the operations. As the designers claimed, the security might be improved as different keys generate different ciphers. This paper analyzes the security of ${\textsf{Magpie}}$, studies the difference propagation of ${\textsf{Magpie}}$, and finally finds that the cipher has a set of $ 2^{80} $ weak keys which makes the full-round encryption weak, and corrects the lower bound of the number of active S-boxes to 10 instead of 25 proposed by the designers. In the weak key model, the security of the cipher is reduced by the claimed $ 2^{80} $ to only $ 4\times2^{16} $.
Linear Complexity of A Family of Binary p2q2-periodic Sequences From Euler Quotients
LUO Bingyu, ZHANG Jingwei, ZHAO Chang’an
, Available online  , doi: 10.23919/cje.2020.00.125
Abstract(180) HTML (82) PDF(19)
Abstract:

A family of binary sequences derived from Euler quotients

\begin{document}$\psi(\cdot)$\end{document}

with RSA modulus

$pq$

is introduced. Here two primes

$p $

and

$q $

are distinct and satisfy

$\gcd(pq, (p-1)(q-1))=1$

. The linear complexities and minimal polynomials of the proposed sequences are determined. Besides, this kind of sequences is shown not to have correlation of order

$four$

, although there exists the following relation

$\psi(t)-\psi(t+p^2q)-\psi(t+q^2p)+\psi(t+(p+q)pq)= $$ 0 \pmod {pq}$

for any integer

$t$

by the properties of Euler quotients.

Quantum Attacks on Type-3 Generalized Feistel Scheme and Unbalanced Feistel Scheme with Expanding Functions
ZHANG Zhongya, WU Wenling, SUI Han, WANG Bolin
, Available online  , doi: 10.23919/cje.2021.00.294
Abstract(264) HTML (125) PDF(27)
Abstract:

Quantum algorithms are raising concerns in the field of cryptography all over the world. A growing number of symmetric cryptography algorithms have been attacked in the quantum setting. Type-3 generalized Feistel scheme (GFS) and unbalanced Feistel scheme with expanding functions (UFS-E) are common symmetric cryptography schemes, which are often used in cryptographic analysis and design. We propose quantum attacks on the two Feistel schemes. For

$ d $

-branch Type-3 GFS and UFS-E, we propose distinguishing attacks on

$(d+1)$

-round Type-3 GFS and UFS-E in polynomial time in the quantum chosen plaintext attack (qCPA) setting. We propose key recovery by applying Grover's algorithm and Simon's algorithm. For

$ r $

-round

$ d $

-branch Type-3 GFS with

$ k $

-bit length subkey, the complexity is

$O({2^{(d - 1)(r - d - 1)k/2}})$

for

$r\ge d + 2$

. The result is better than that based on exhaustive search by a factor

${2^{({d^2} - 1)k/2}}$

. For

$ r $

-round

$ d $

-branch UFS-E, the attack complexity is

$O({2^{(r - d - 1)(r - d)k/4}})$

for

$d + 2 \le r \le 2d$

, and

$O({2^{(d - 1)(2r - 3d)k/4}})$

for

$r > 2d$

. The results are better than those based on exhaustive search by factors

${2^{(4rd - {d^2} - d - {r^2} - r)k/4}}$

and

${2^{3(d - 1)dk/4}}$

in the quantum setting, respectively.

ARTIFICIAL INTELLIGENCE
Adaptive Tensor Rank Approximation for Multi-view Subspace Clustering
SUN Xiaoli, HAI Yang, ZHANG Xiujun, XU Chen
, Available online  , doi: 10.23919/cje.2022.00.180
Abstract(18) HTML (9) PDF(6)
Abstract:
Multi-view subspace clustering under a tensor framework remains a challenging problem, which can be potentially applied to image classification, impainting, denoising, etc. There are some existing tensor-based multi-view subspace clustering models mainly making use of the consistency in different views through tensor nuclear norm (TNN). The diversity which means the intrinsic difference in individual view is always ignored. In this paper, a new tensorial multi-view subspace clustering model is proposed, which jointly exploits both the consistency and diversity in each view. The view representation is decomposed into view-consistent part (low-rank part) and view-specific part (diverse part). A tensor adaptive log-determinant regularization (TALR) is imposed on the low-rank part to better relax the tensor multi-rank, and a view-specific sparsity regularization is applied on the diverse part to ensure connectedness property. Although the TALR minimization is not convex, it has a closed-form analytical solution and its convergency is validated mathematically. Extensive evaluations on six widely used clustering datasets are executed and our model is demonstrated the superior performance.
Representation of Semantic Word Embeddings Based on SLDA and Word2vec Model
TANG Huanling, ZHU Hui, WEI Hongmin, ZHENG Han, MAO Xueli, LU Mingyu, GUO Jin
, Available online  , doi: 10.23919/cje.2021.00.113
Abstract(327) HTML (149) PDF(26)
Abstract:

To solve the problem of semantic loss in text representation, this paper proposes a new embedding method of word representation in semantic space called wt2svec based on supervised latent Dirichlet allocation (SLDA) and Word2vec. It generates the global topic embedding word vector utilizing SLDA which can discover the global semantic information through the latent topics on the whole document set. It gets the local semantic embedding word vector based on the Word2vec.  The new semantic word vector is obtained by combining the global semantic information with the local semantic information. Additionally, the document semantic vector named doc2svec is generated. The experimental results on different datasets show that wt2svec model can obviously promote the accuracy of the semantic similarity of words, and improve the performance of text categorization compared with Word2vec.

Improving Cross-Corpus Speech Emotion Recognition using Deep Local Domain Adaptation
ZHAO Huijuan, YE Ning, WANG Ruchuan
, Available online  , doi: 10.23919/cje.2021.00.196
Abstract(140) HTML (65) PDF(16)
Abstract:

Due to insufficient data and high cost of data annotation, it is usually necessary to use knowledge transfer to recognize speech emotion. However, the uncertainty and subjectivity of emotion make speech emotion recognition based on transfer learning more challenging. Domain adaptation based on maximum mean discrepancy considers the marginal alignment of source domain and target domain, but without paying regard to the class prior distribution in both domains, which reduces the transfer efficiency. To solve this problem, a novel cross-corpus speech emotion recognition framework based on local domain adaption is proposed, in which a local weighted maximum mean discrepancy is used to evaluate the distance between different emotion datasets. Experimental results show that the cross-corpus speech emotion recognition has been improved when compared with other cross-corpus methods including global domain adaptation and cross-corpus speech emotion recognition directly.

COMMUNICATIONS
Frame Synchronization Method Based on Association Rules for CNAV-2 Messages
LI Xinhao, MA Tao, QIAN Qishu
, Available online  , doi: 10.23919/cje.2021.00.148
Abstract(170) HTML (74) PDF(10)
Abstract:
The GPS system is a navigation satellite system with high precision, all-weather service, and global coverage, whose main purpose is to provide real-time and continuous global navigation services for the US military, and whose signal interference in wartime is a heavy blow to the US military. Its existing interference measures are classified into two types: blanket jamming and deception jamming, with the latter having better interference effects due to its imperceptibility. Frame synchronization, as the foundation of deception jamming, is a focus of current research on navigation countermeasures. This paper discusses the frame synchronization of CNAV-2 messages in GPS L1C signals and proposes a frame synchronization algorithm based on association rules. It analyzes the structural characteristics of CNAV-1 message data, reveals the hidden mapping relationships in the BCH code sequence of the first sub-frame by applying association rules, and achieves a blind synchronization of navigation messages by counting the types of mapping relationships and calculating the confidence levels. The simulation test results show that the proposed algorithm displays high error resilience and correct recognition rates and demonstrates certain values in engineering applications.
A Beam-Steering Broadband Microstrip Antenna with High Isolation
JIANG Zhaoneng, SHA Yongxin, NIE Liying, XUAN Xiaofeng
, Available online  , doi: 10.23919/cje.2021.00.452
Abstract(119) HTML (60) PDF(19)
Abstract:
In this paper, a 4.2–7.2 GHz (52.6%) beam-steering microstrip antenna was proposed. The proposed antenna consists of three tapered slots and feeds. The three radiation directions of the antenna on the plane are independent of each other, and the three feeds correspond to the three radiation structures. Symmetry isolation trenches are introduced to improve isolation between different ports. Radiation pattern simulation and measurement show horizontal beam steering at the sampled frequencies of 4.2, 5, 6, and 7.2 GHz. The results shows that the overlapped beam of the three ports in the E-plane and H-plane can cover more than 200 degrees and 60 degrees, respectively. Apart from the capability of beam-steering, high isolation (mor than 28 dB) of the proposed antenna in the operating band is obtained.
LBA-EC: Load Balancing Algorithm Based on Weighted Bipartite Graph for Edge Computing
SHAO Sisi, LIU Shangdong, LI Kui, YOU Shuai, QIU Huajie, YAO Xiaoliang, JI Yimu
, Available online  , doi: 10.23919/cje.2021.00.289
Abstract(335) HTML (146) PDF(25)
Abstract:
Compared with cloud computing environment, edge computing has many choices of service providers due to different deployment environments. The flexibility of edge computing makes the environment more complex. The current edge computing architecture has the problems of scattered computing resources and limited resources of single computing node. When the edge node carries too many task requests, the makespan of the task will be delayed. We propose a load balancing algorithm based on weighted bipartite graph for edge computing (LBA-EC), which makes full use of network edge resources, reduces user delay, and improves user service experience. The algorithm is divided into two phases for task scheduling. In the first phase, the tasks are matched to different edge servers. In the second phase, the tasks are optimally allocated to different containers in the edge server to execute according to the two indicators of energy consumption and completion time. The simulations and experimental results show that our algorithm can effectively map all tasks to available resources with a shorter completion time.
Ergodic Capacity of NOMA-Based Overlay Cognitive Integrated Satellite-UAV-Terrestrial Networks
GUO Kefeng, LIU Rui, DONG Chao, AN Kang, HUANG Yuzhen, ZHU Shibing
, Available online  , doi: 10.23919/cje.2021.00.316
Abstract(88) HTML (44) PDF(19)
Abstract:
Satellite communication has become a popular study topic owing to its inherent advantages of high capacity, large coverage, and no terrain restrictions. Also, it can be combined with terrestrial communication to overcome the shortcomings of current wireless communication, such as limited coverage and high destructibility. In recent years, the integrated satellite-unmanned aerial vehicle-terrestrial networks (IS-UAV-TNs) have aroused tremendous interests to effectively reduce the transmission latency and enhance quality-of-service with improved spectrum efficiency. However, the rapidly growing access demands and conventional spectrum allocation scheme lead to the shortage of spectrum resources. To tackle the mentioned challenge, the non-orthogonal multiple access (NOMA) scheme and cognitive radio technique are utilized in IS-UAV-TN, which can improve spectrum utilization. In our paper, the transmission capacity of an NOMA-enabled IS-UAV-TN under overlay mode is discussed, specifically, we derive the closed-form expressions of ergodic capacity for both primary and secondary networks. Besides, simulation results are provided to demonstrate the validity of the mathematical derivations and indicate the influences of critical system parameters on transmission performance. Furthermore, the orthogonal multiple access (OMA)-based scheme is compared with our NOMA-based scheme as a benchmark, which illustrates that our proposed scheme has better performance.
Technique for Recovering Wavefront Phase Bad Points by Deep Learning
WU Jiali, LIANG Jingyuan, FEI Shaolong, ZHONG Xirui
, Available online  , doi: 10.23919/cje.2022.00.008
Abstract(94) HTML (49) PDF(5)
Abstract:
In adaptive optics systems, the bad spot detected by the wavefront detector affects the wavefront reconstruction accuracy. A convolutional neural network (CNN) model is established to estimate the missing information on bad points, reduce the reconstruction error of the distorted wavefront. By training 10,000 groups of spot array images and the corresponding 30th order Zernike coefficient samples, learns the relationship between the light intensity image and the Zernike coefficient, and predicts the Zernike mode coefficient based on the spot array image to restore the wavefront. Following the wavefront restoration of 1,000 groups of test set samples, the root mean square (RMS) error between the predicted value and the real value was maintained at approximately 0.2 μ m. Field wavefront correction experiments were carried out on three links of 600 m, 1.3 km, and 10 km. The wavefront peak-to-valley values corrected by the CNN decreased from 12.964 µ m, 13.958 µ m, and 31.310 µ m to 0.425 µ m, 3.061 µ m, and 11.156 µ m, respectively, and the RMS values decreased from 2.156 µ m, 9.158 µ m, and 12.949 µ m to approximately 0.166 µ m, 0.852 µ m, and 6.963 µ m, respectively. The results show that the CNN method predicts the missing wavefront information of the sub-aperture from the bad spot image, reduces the wavefront restoration error, and improves the wavefront correction performance.
MADRL-Based 3D Deployment and User Association of Cooperative mmWave Aerial Base Stations for Capacity Enhancement
ZHAO Yikun, ZHOU Fanqin, FENG Lei, LI Wenjing, YU Peng
, Available online  , doi: 10.23919/cje.2021.00.327
Abstract(236) HTML (110) PDF(25)
Abstract:
Although millimeter-wave aerial base station (mAeBS) gains rich wireless capacity, it is technically difficult for deploying several mAeBSs to solve the surge of data traffic in hotspots when considering the amount of interference from neighboring mAeBS. This paper introduces coordinated multiple points transmission (CoMP) into the mAeBS-assisted network for capacity enhancement and designs a two-timescale approach for three-dimensional (3D) deployment and user association of cooperative mAeBSs. Specially, an affinity propagation clustering based mAeBS-user cooperative association scheme is conducted on a large timescale followed by modeling the capacity evaluation, and a deployment algorithm based on multi-agent deep deterministic policy gradient (MADDPG) is designed on the small timescale to obtain the 3D position of mAeBS in a distributed manner. Simulation results demonstrate that the proposed approach has significant throughput gains over conventional schemes without CoMP, and the MADDPG is more efficient than centralized deep reinforcement learning algorithms in deriving the solution.
Self-adaptive Discrete Cuckoo Search Algorithm for the Service Routing Problem with Time Windows and Stochastic Service Time
OU Xianfeng, WU Meng, LI Wujing, ZHANG Guoyun, XIE Wenwu
, Available online  , doi: 10.23919/cje.2022.00.072
Abstract(27) HTML (13) PDF(5)
Abstract:
Making house calls is very crucial to deal with the competitive pressures of the service business and to improve service quality. We design a model called service routing problem with time windows and stochastic service time (SRPTW-SST) that is based on vehicle routing problem with time windows (VRPTW). A self-adaptive discrete Cuckoo Search Algorithm with genetic mechanism (sDCS-GM) is proposed for the SRPTW-SST. We design a selection mechanism to improve the logicality of the algorithm based on the strong randomness of the Lévy flight. We introduce a genetic mechanism and design a neighborhood search mechanism for improving the robustness of the algorithm. An adaptive parameter adjustment method is designed to eliminate the impact of fixed parameters. The experimental results show that the sDCS-GM algorithm is more robust and effective than the state-of-the-art methods.
A verifiable multi-secret sharing scheme based on short integer solution
LI Fulin, YAN Jiayun, ZHU Shixin, HU Hang
, Available online  , doi: 10.23919/cje.2021.00.062
Abstract(37) HTML (18) PDF(8)
Abstract:
The threshold secret sharing scheme plays a very important role in cloud computing and group communication. With the possible birth of the quantum computer, traditional secret sharing schemes have been unable to meet security requirements. We proposed a new verifiable multi-secret sharing scheme based on the short integer solution problem. By utilizing a symmetric binary polynomial, $ k $ secrets and secret shares can be generated, and then we convert the secret shares into binary string on $ \mathbb{Z}_q $, which can be identified by one-way anti-collision hash function on the lattice, so that multiple secrets can be reconstructed safely. The advantages mainly focus on verifiability without interaction in the distribution phase and less memory requirement. In a secret sharing scheme, verifiability prevents the dealer to share the wrong shares and forces the participants to submit their shares correctly. Meanwhile, the interaction between dealer and participant (participant and participant) can be reduced, which means the security is improved. In a multi-secret sharing scheme, releasing the public values is inevitable, this paper has less public values and less size of shares per secret size to reduce the pressure of memory consumption in the proper parameters. In the end, based on the short integer solution problem, this paper can also effectively resist the quantum attack.
Remote Data Auditing for Cloud-Assisted WBANs with Pay-as-you-go Business Model
LI Yumei, ZHANG Futai
, Available online  , doi: 10.23919/cje.2020.00.314
Abstract(137) HTML (67) PDF(10)
Abstract:
As an emerging technology, cloud-assisted Wireless Body Area Networks (WBANs) provide more convenient services to users. Recently, many remote data auditing (RDA) protocols have been proposed to ensure the data integrity and authenticity when data owners outsourced their data to the cloud. However, most of them cannot check data integrity periodically according to the pay-as-you-go business model. These protocols also need high tag generation computation overhead, which brings a heavy burden for data owners. Therefore, we construct a lightweight remote data auditing protocol to overcome all above drawbacks. Our work can be deployed in the public environment without secret channels. It makes use of certificate-based cryptography which gets rid of certificate management problems, key escrow problems, and secret channels. The security analysis illustrates that the proposed protocol is secure. Moreover, the performance evaluation implies that our work is available in cutting down computation and communication overheads.
Internet of Brain, Thought, Thinking, and Creation
ZHANG Zhimin, YIN Rui, NING Huansheng
, Available online  , doi: 10.23919/cje.2021.00.236
Abstract(499) HTML (231) PDF(53)
Abstract:

Thinking space came into being with the emergence of human civilization. With the emergence and development of cyberspace, the interaction between those two spaces began to take place. In the collision of thinking and technology, new changes have taken place in both thinking space and cyberspace. To this end, this paper divides the current integration and development of thinking space and cyberspace into three stages, namely Internet of brain (IoB), Internet of thought (IoTh), and Internet of thinking (IoTk). At each stage, the contents and technologies to achieve convergence and connection of spaces are discussed. Besides, the Internet of creation (IoC) is proposed to represent the future development of thinking space and cyberspace. Finally, a series of open issues are raised, and they will become thorny factors in the development of the IoC stage.

AUTOMATION & CONTROL SYSTEMS
A Dynamic Hysteresis Model of Piezoelectric Ceramic Actuators
DONG Ruili, TAN Yonghong, XIE Yingjie, LI Xiaoli
, Available online  , doi: 10.23919/cje.2021.00.273
Abstract(84) HTML (42) PDF(15)
Abstract:

A modified Prandtl-Ishlinskii (PI) model with rate-dependent thresholds for describing the hysteresis characteristics of piezoelectric actuators is proposed. Based on the classical PI model, a novel threshold depending on the input rate is constructed. With the novel rate-dependent threshold, the play operator has the capability to track the frequency variation of the input signal. Thus, the proposed modified PI model can be used to depict the rate-dependent hysteresis of piezoelectric actuators. Finally, experimental results are presented to show the model validation results of the proposed modeling method.

CIRCUITS & SYSTEMS
A Novel Method for Maximum Power Point Tracking of the Grid-Connected Three-Phase Solar Systems Based on the PV Current Prediction
Saeid Bairami, Mahdi Salimi, Davar Mirabbasi
, Available online  , doi: 10.23919/cje.2021.00.218
Abstract(81) HTML (39) PDF(12)
Abstract:

In this paper, it is first attempted to provide a small signal model of the photovoltaic (PV) system, DC-DC boost converter, and pulse width modulation generator. Then, a technique is provided for maximum power point tracking in grid-connected solar systems based on variable and adaptive perturbation and observation with PV current predictive control. An innovative aspect of the proposed current predictive control method is to use the current predictive control to achieve the value of PV inductance based on PV current predictive model, which has been used in DC-DC boost converter. The proposed method is to obtain the coming current value on the basis of the current predictive model. The goal of the proposed method is to make the DC-DC boost converter inductor current track the current reference. Voltage and current ripple minimization is added to the cost function simultaneously as a system constraint to optimize system performance. This reduces the amount of voltage and current fluctuations around the maximum power point. The proposed method is capable of detecting rapid changes in solar radiation. A sudden and simultaneous increase in voltage and current is detected by the algorithm and then the duty cycle becomes increasing instead of decreasing. The simulation is carried out in MATLAB Simulink environment in real-time for a 26.6 kW three-phase grid-connected solar system. The simulation results of current predictive control are compared with perturbation and observation techniques and linear voltage and current proportional integral derivative (PID) controller-based adaptive control. The results show that the total harmonic distortion (THD%) of the inverter voltage with proposed method has been reduced by 0.16% compared to the PID method. In addition, the THD% of the current in the proposed method is reduced by 0.1% compared to the PID method. The solar system output voltage variation of the proposed method is less than 5 V.

IIMAGE AND SIGNAL PROCESSING
A Directly Readable Halftone Multifunctional Color QR Code
HUANG Yuan, CAO Peng, LV Guangwu
, Available online  , doi: 10.23919/cje.2021.00.366
Abstract(156) HTML (78) PDF(18)
Abstract:

Color quick response (QR) code is an important direction for the future development of QR code, which has become a research hotspot due to the additional functional characteristics of its colors as the wide application of QR code technology. The existing color QR code has solved the problem of information storage capacity, but it requires an enormous hardware and software support system, making how to achieve its direct readability an urgent issue. This paper proposes a novel color QR code that combines multiple types of different identification information. This code combines multiplexing and color-coding technology to present the publicly encoded information (such as advertisements, public query information) as plain code, and traceability, blockchain, anti-counterfeiting authentication and other information concealed in the form of hidden code. We elaborate the basic principle of this code, construct its mathematical model and supply a set of algorithm design processes, which breakthrough key technology of halftone printout. The experimental results show that the proposed color QR code realizes the multi-code integration and can be read directly without special scanning equipment, which has unique advantages in the field of printing anti-counterfeiting labels.

Radar
An Adaptive Interactive Multiple-Model Algorithm Based on End-to-End Learning
ZHU Hongfeng, XIONG Wei, CUI Yaqi
, Available online  , doi: 10.23919/cje.2021.00.442
Abstract(130) HTML (63) PDF(6)
Abstract:

The interactive multiple-model (IMM) is a popular choice for target tracking. However, to design transition probability matrices (TPMs) for IMMs is a considerable challenge with less prior knowledge, and the TPM is one of the fundamental factors influencing IMM performance. IMMs with inaccurate TPMs can make it difficult to monitor target maneuvers and bring poor tracking results. To address this challenge, we propose an adaptive IMM algorithm based on end-to-end learning. In our method, the neural network is utilized to estimate TPMs in real-time based on partial parameters of IMM in each time step, resulting in a generalized recurrent neural network. Through end-to-end learning in the tracking task, the dataset cost of the proposed algorithm is smaller and the generalizability is stronger. Simulation and automatic dependent surveillance-broadcast (ADS-B) tracking experiment results show that the proposed algorithm has better tracking accuracy and robustness with less prior knowledge.

SIGNAL PROCESSING & BIOINFOMATICS
Gmean Maximum FSVMI Model and Its Application for Carotid Artery Stenosis Risk Prediction
ZHANG Xueying, GUO Yuling, LI Fenglian, WEI Xin, HU Fengyun, HUI Haisheng, JIA Wenhui
, Available online  , doi: 10.23919/cje.2020.00.185
Abstract(186) HTML (79) PDF(10)
Abstract:

Carotid artery stenosis is a serious medical condition that can lead to stroke. Using machine learning method to construct classifier model, carotid artery stenosis can be diagnosed with transcranial doppler data. We propose an improved fuzzy support vector machine (FSVMI) model to predict carotid artery stenosis, with the maximum geometric mean (Gmean) as the optimization target. The fuzzy membership function is obtained by combining information entropy with the normalized class-center distance. Experimental results showed that the proposed model was superior to the benchmark models in sensitivity and geometric mean criteria.

ANTENNAS
Design of Pyramidal Horn with Arbitrary E\H Plane Half-Power Beamwidth
ZHANG Wenrui, SHAO Wenyuan, JI Yicai, LI Chao, YANG Guan, LU Wei, FANG Guangyou
, Available online  , doi: 10.23919/cje.2021.00.212
Abstract(342) HTML (150) PDF(12)
Abstract:

This paper proposed a novel design method for pyramid horns which are under the constraints of 3 dB beamwidth. It is based on the general radiation patterns of E\H planes derived from Huygens’ principle. Through interpolation and fitting techniques, the E\H plane’s maximum aperture error parameter of the pyramid horn is obtained as a function of the angle and aperture electrical size. Firstly, the aperture size of the E (or H) plane is calculated with the help of the optimal gain principle. Secondly, the constraint equation of another plane is derived. Finally, the intersection of constraint equation and interpolation function, which can be solved iteratively, contains all the solution information. The general radiation patterns neglect the influence of the Huygens element factor which makes the error bigger in large design beamwidth. In this paper, through theoretical analysis and simulation experiments, two correction formulas are employed to correct the Huygens element factor’s influence on the E\H planes. Simulation experiments and measurements show that the proposed method has a smaller design error in the range of 0–60 degrees half-power beamwidth.

Electromagnetic & Microwave
Design and Realization of Broadband Active Inductor Based Band Pass Filter
Aysu Belen, Mehmet A. Belen, Merih Palandöken, Peyman Mahouti, Özlem Tari
, Available online  , doi: 10.23919/cje.2021.00.322
Abstract(99) HTML (46) PDF(11)
Abstract:

With the latest developments in the wireless communication systems, the alternative design methodologies are required for the broadband design of microwave components. In this paper, a compact broad band pass filter (BPF) design is introduced through the microwave design technique based on the active inductor (AIN) with the numerical computation and experimental measurement studies. The proposed AIN based BPF has operating frequency band extending from 0.8 GHz to 2.7 GHz in compact size with high selectivity in comparison to conventional LC based BPF. The experimental measurement results agree well with the numerical computation results. The proposed AIN based BPF design has technical capability to be conveniently tuned to operate at different frequency bands.