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Published in: Chinese Journal of Electronics

(Volume: 30, Issue: 6, 05 November 2021)

Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
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Statistical Model on CRAFT
WANG Caibing, GUO Hao, YE Dingfeng, WANG Ping
 doi: 10.1049/cje.2021.00.092
Abstract(87) HTML(48) PDF(11)
Many cryptanalytic techniques for symmetric-key primitives rely on specific statistical analysis to extract some secrete key information from a large number of known or chosen plaintext-ciphertext pairs. For example, there is a standard statistical model for differential cryptanalysis that determines the success probability and complexity of the attack given some predefined configurations of the attack. In this work, we investigate the differential attack proposed by Guo et al. at Fast Software Encryption Conference 2020 and find that in this attack, the statistical behavior of the counters for key candidates deviate from standard scenarios, where both the correct key ${\boldsymbol{k}}$ and ${\boldsymbol{k \oplus XXX}}$ are expected to receive the largest number of votes. Based on this bimodal behavior, we give three different statistical models for truncated differential distinguisher on CRAFT (a cryptographic algorithm proposed by Beierle et al. in IACR Transactions on Symmetric Cryptology in 2019) for bimodal phenomena. Then, we provide the formulas about the success probability and data complexity for different models under the condition of a fixed threshold value. Also, we verify the validity of our models for bimodal phenomena by experiments on round-reduced of the versions distinguishers on CRAFT. We find that the success probability of theory and experiment are close when we fix the data complexity and threshold value. Finally, we compare the three models using the mathematical tool Matlab and conclude that Model 3 has better performance.
Investigation and Comparison of 5G Channel Models: From QuaDRiGa, NYUSIM, and MG5G Perspectives
PANG Lihua, ZHANG Jin, ZHANG Yang, HUANG Xinyi, CHEN Yijian, LI Jiandong
 doi: 10.1049/cje.2021.00.103
Abstract(106) HTML(53) PDF(13)
This paper investigates and compares three channel models for 5G wireless communications: the Quasi deterministic radio channel generator (QuaDRiGa), the NYUSIM channel model developed by New York University (NYU), and the More general 5G (MG5G) channel model. First, the characteristics of the modeling processes of the three models are introduced from the perspective of model framework. Then, the small-scale parameter modeling strategies of the three models are compared from space/time/frequency domains as well as polarization aspect. In particular, the drifting of small-scale parameters is introduced in detail. Finally, through the simulation results of angular power spectrum, doppler power spectrum density, temporal autocorrelation function, power delay profile, frequency correlation function, channel capacity, and eigenvalue distribution, the three models are comprehensively investigated. According to the simulation results, we clearly analyze the impact of the modeling strategy on the three channel models and give certain evaluations and suggestion which lay a solid foundation for link and system-level simulations for 5G transmission algorithms.
Based on Weight and User Feedback: A Novel Trustworthiness Measurement Model
ZHOU Wei, MA Yanfang, PAN Haiyu
 doi: 10.1049/cje.2020.00.391
Abstract(213) HTML(103) PDF(20)
Software trustworthiness is an important criterion for evaluating software quality. In component-based software, different components play different roles and different users give different grades of trustworthiness after using the software. These elements will both affect the trustworthiness of software. When the software quality is evaluated comprehensively, it is necessary to consider the weight of component and user feedback. According to different construction of components, the different trustworthiness measurement models are established based on the weight of components and user feedback. Algorithms of these trustworthiness measurement models are designed in order to obtain the corresponding trustworthiness measurement value automatically. The feasibility of these trustworthiness measurement models is demonstrated by a train ticket purchase system.
WCM-WTrA: A Cross-Project Defect Prediction Method Based on Feature Selection and Distance-Weight Transfer Learning
LEI Tianwei, XUE Jingfeng, WANG Yong, NIU Zequn, SHI Zhiwei, ZHANG Yu
 doi: 10.1049/cje.2021.00.119
Abstract(105) HTML(48) PDF(13)
Cross-project defect prediction is a hot topic in the field of defect prediction. How to reduce the difference between projects and make the model have better accuracy is the core problem. This paper starts from two perspectives: feature selection and distance-weight instance transfer. We reduce the differences between projects from the perspective of feature engineering and introduce the transfer learning technology to construct a cross-project defect prediction model WCM-WtrA and multi-source model Multi-WCM-WTrA. We have tested on AEEEM and ReLink datasets, and the results show that our method has an average improvement of 23% compared with TCA + algorithm on AEEEM datasets, and an average improvement of 5% on ReLink datasets.
A Survey: FPGA-Based Dynamic Scheduling of Hardware Tasks
LI Tianyang, ZHANG Fan, GUO Wei, et al.
2021, 30(6): 991-1007.   doi: 10.1049/cje.2021.07.021
Abstract(91) PDF(38)
To meet the increasing computing needs of various application fields, Field programmable gate array (FPGA) has been widely deployed. In FPGA-based processing, hardware tasks can be better accelerated by allocating appropriate computing resources. Therefore, FPGA-based hardware task scheduling has become one of the mainstream research directions in academia and industry. However, the optimization objectives of existing FPGA-based hardware task scheduling methods are relatively scattered. In this regard, this paper summarizes the research status of hardware task dynamic scheduling from the three essential elements of FPGA processing:time, resources, and power consumption. This paper analyzes, sorts out, categorizes the ideas and implementations of various scheduling methods and analyzes and evaluates optimization effects of various scheduling methods from multiple dimensions. Then, the shortcomings of the existing methods are summarized and some practical applications are introduced. Finally, the research direction of task scheduling based on FPGA is prospected and summarized.
An Parallel FPGA SAT Solver Based on Multi-Thread and Pipeline
LI Tiejun, MA Kefan, ZHANG Jianmin
2021, 30(6): 1008-1016.   doi: 10.1049/cje.2021.08.001
Abstract(32) PDF(14)
The Boolean Satisfiability (SAT) problem is the key problem in computer theory and application. A parallel multi-thread SAT solver named pprobSAT+ on a configurable hardware is proposed. In the algorithm, multithreads are executed simultaneously to hide the circuit stagnate. In order to improve the working frequency and throughput of the SAT solver, the deep pipeline strategy is adopted. When all data stored in block random access memory of the field programmable gate array, the solver can achieve maximum performance. If partial data are stored in the external memory, the size of the problem instances the SAT solver can be greatly improved. The experimental results show that the speedup of three-thread SAT solver is approximately 2.4 times with single thread, and shows that the pprobSAT+ have achieved substantial improvement while a solution is found.
Ultra-thin Body Buried In0.35Ga0.65As Channel MOSFETs with Extremely Low Off-current on Si Substrates
WANG Bo, DING Peng, FENG Ruize, et al.
2021, 30(6): 1017-1021.   doi: 10.1049/cje.2021.07.024
Abstract(51) PDF(16)
In this paper, we investigated the electrical properties of the Metal-oxide-semiconductor gate stack of Ti/Al2O3/InP under different annealing conditions. A minimum interface trap density of 3×1011cm-2eV-1 is obtained without postmetallization annealing treatment. Additionally, utilizing Ti/Al2O3/InP MOS gate stack, we fabricated ultra-thin body buried In0.35Ga0.65As channel MOSFETs on Si substrates with optimized on/off trade-off. The 200nm gate length device with extremely low off-current of 0.6nA/µm, and on-off ratio of 3.3×105, is demonstrated by employing buried low indium (In0.35Ga0.65As) channel with InP barrier/spacer device structure, giving strong potential for future highperformance and low-power applications.
New Secondary Constructions of Generalized Bent Functions
YANG Zhiyao, KE Pinhui, CHEN Zhixiong
2021, 30(6): 1022-1029.   doi: 10.1049/cje.2021.08.003
Abstract(50) PDF(12)
Three new secondary constructions of generalized bent functions are presented. We provide a secondary construction of generalized bent functions from indirect sum methods proposed by Carlet et al. A new secondary construction of generalized bent functions from four initial functions is also investigated. We demonstrate that many known constructions can be derived from our proposed construction as special cases by choosing proper initial functions and parameters. By modifying the new construction, a novel secondary construction of generalized bent functions from two initial generalized bent functions is obtained. For the binary case, the dual functions of the bent functions by our method are presented, which share the same formula as the indirect sum.
Quantum Differential Collision Distinguishing Attacks on Feistel Schemes
ZHANG Zhongya, WU Wenling, WANG Bolin
2021, 30(6): 1030-1037.   doi: 10.1049/cje.2021.07.026
Abstract(44) PDF(14)
Feistel schemes are important components of symmetric ciphers, which have been extensively studied in the classical setting. We examine the extension methods of differential distinguishers of Feistel key-function and Feistel function-key schemes. The schemes are subjected to quantum differential collision distinguishing attacks based on the methods. The results show that the complexity is lower than that of differential attacks using only Grover algorithm, and the complexity of differential collision attack based on the Brassard-Høyer-Tapp and Grover algorithms is lower than that of quantization when using only the Grover algorithm. The results also show that different algorithms and methods can be combined to produce a more effective cryptanalysis approach. This provides a research direction for postquantum cryptographic analysis and design.
Video-Driven 2D Character Animation
YIN Qinran, CAO Weiqun
2021, 30(6): 1038-1048.   doi: 10.1049/cje.2021.07.016
Abstract(12) PDF(6)
Video-driven animation has always been a hot and challenging topic in the field of computer animation. We propose a method of mapping a sequence of human skeletal keypoints in a video onto a two-dimensional character to generate 2D character animation. For a given two-dimensional character picture, we extract the motion of real human in video data, driving the character deformation. We analyze common two-dimensional human body movements, classify the basic posture of the human body, realize the recognition of skeleton posture based on back propagation network, capture human body motion by automatically tracking the position of the human skeleton keypoints coordinates in the video and redirect the motion data to a 2D character. Compared with the traditional method, our work is less affected by video data illumination and background complexity. We calibrate human body motion in videos to a 2D character according to the skeleton topology to avoid motion distortion caused by the difference in skeleton size and ratio. The experimental results show that the proposed algorithm can generate the motion of two-dimensional characters based on the motion of human characters in video data. The animation is natural and smooth, and the algorithm has strong robustness.
Standard Analysis for Transfer Delay in CTCS-3
CAO Yuan, MA Lianchuan, XIAO Shuo, ZHANG Xia, XU Wei
2017, 26(5): 1057-1063.   doi: 10.1049/cje.2017.08.024
[Abstract](256) [PDF 634KB](368)
According to the standard for the GSM for railway (GSM-R) wireless systems in China train control system level 3 (CTCS-3), the control data transfer delay should be no larger than 500ms with greater than 99% probability. Coverage of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals (MTs) and redundant MTs on one train are considered, and the corresponding vehicle-ground communication models, delay models, and fault models are constructed. The simulation results confirm that the transfer delay can meet the standard requirements under all cases. In particular, the probability is greater than 99.996% for redundant MTs and networks, and the standard of transfer delay in CTCS-3 will be improved inevitably.
A Survey on Emerging Computing Paradigms for Big Data
ZHANG Yaoxue, REN Ju, LIU Jiagang, XU Chugui, GUO Hui, LIU Yaping
2017, 26(1): 1-12.   doi: 10.1049/cje.2016.11.016
[Abstract](332) [PDF 1424KB](2639)
The explosive growth of data volume and the ever-increasing demands of data value extraction have driven us into the era of big data. The "5V" (Variety, Velocity, Volume, Value, and Veracity) characteristics of big data pose great challenges to traditional computing paradigms and motivate the emergence of new solutions. Cloud computing is one of the representative technologies that can perform massive-scale and complex data computing by taking advantages of virtualized resources, parallel processing and data service integration with scalable data storage. However, as we are also experiencing the revolution of Internet-of-things (IoT), the limitations of cloud computing on supporting lightweight end devices significantly impede the flourish of cloud computing at the intersection of big data and IoT era. It also promotes the urgency of proposing new computing paradigms. We provide an overview on the topic of big data, and a comprehensive survey on how cloud computing as well as its related technologies can address the challenges arisen by big data. Then, we analyze the disadvantages of cloud computing when big data encounters IoT, and introduce two promising computing paradigms, including fog computing and transparent computing, to support the big data services of IoT. Finally, some open challenges and future directions are summarized to foster continued research efforts into this evolving field of study.
Clustering by Fast Search and Find of Density Peaks with Data Field
WANG Shuliang, WANG Dakui, LI Caoyuan, LI Yan, DING Gangyi
2016, 25(3): 397-402.   doi: 10.1049/cje.2016.05.001
[Abstract](431) [PDF 6951KB](2513)
A clustering algorithm named "Clustering by fast search and find of density peaks" is for finding the centers of clusters quickly. Its accuracy excessively depended on the threshold, and no efficient way was given to select its suitable value, i.e., the value was suggested be estimated on the basis of empirical experience. A new way is proposed to automatically extract the optimal value of threshold by using the potential entropy of data field from the original dataset. For any dataset to be clustered, the threshold can be calculated from the dataset objectively instead of empirical estimation. The results of comparative experiments have shown the algorithm with the threshold from data field can get better clustering results than with the threshold from empirical experience.
Optimization of Information Interaction Protocols in Cooperative Vehicle-Infrastructure Systems
ZHANG Yuzhuo, CAO Yuan, WEN Yinghong, LIANG Liang, ZOU Feng
2018, 27(2): 439-444.   doi: 10.1049/cje.2017.10.009
[Abstract](103) [PDF 566KB](323)
This research investigate the information interaction protocols for Cooperative vehicleinfrastructure systems (CVIS) safety-related services and optimizes them in three aspects. It puts forward a selfadaptive back-off algorithm. This algorithm considers retransmission times and network busy degree to choose a suitable contention window. A mathematical analysis model is developed to verify its performance improvement. Finally, different scenario models of Vehicle ad hoc network (VANET) are simulated through the network simulation tool and the influences of different access modes on Quality of Service (QoS) are investigated. The simulation results have verified the improvement of the proposed algorithm is obvious and RTS/CTS access mode can sacrifice slight delay for great improvement of packet lost rate when there are large amount of vehicle nodes.
Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine
SHU Jian, LIU Song, LIU Linlan, ZHAN Liqin, HU Gang
2017, 26(2): 377-384.   doi: 10.1049/cje.2017.01.013
[Abstract](99) [PDF 1133KB](504)
In the application of Wireless sensor networks (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality estimation mechanism is proposed, which is based on Support vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive signal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link quality is divided into five levels according to Packet reception rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial respectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reasonable. Compared with the recent published link quality estimation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.
Optimal Network Function Virtualization and Service Function Chaining: A Survey
MIRJALILY Ghasem, LUO Zhiquan
2018, 27(4): 704-717.   doi: 10.1049/cje.2018.05.008
[Abstract](263) [PDF 827KB](879)
Network function virtualization (NFV) and Service function chaining (SFC) can fulfill the traditional network functions by simply running special softwares on general-purpose computer servers and switches. This not only provides significantly more agility and flexibility in network service deployment, but can also greatly reduce the capital and operating cost of networks. In this paper, a comprehensive survey on the motivations and state of the art efforts towards implementing the NFV and SFC is provided. In particular, the paper first presents the main concepts of these new emerging technologies; then discusses in details various stages of SFC, including the description, composition, placement and scheduling of service chains. Afterwards, existing approaches to SFC are reviewed according to their application environments, parameters used, and solution strategies. Finally, the paper points out a number of future research directions.
A Text Sentiment Classification Modeling Method Based on Coordinated CNN-LSTM-Attention Model
ZHANG Yangsen, ZHENG Jia, JIANG Yuru, HUANG Gaijuan, CHEN Ruoyu
2019, 28(1): 120-126.   doi: 10.1049/cje.2018.11.004
[Abstract](150) [PDF 1983KB](1046)
The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document. We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information. Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.
Performance Evaluation with Improved Receiver Design for Asynchronous Coordinated Multipoint Transmissions
CAO Yuan, WEN Yinghong, MENG Xiangyang, XU Wei
2016, 25(2): 372-378.   doi: 10.1049/cje.2016.03.026
[Abstract](138) [PDF 411KB](1126)
Joint transmission is one of the major transmission schemes in Coordinated multipoint (CoMP) transmission/reception systems for Long term evolutionadvanced (LTE-A). Due to different distances between User equipments (UE) and Base stations (BS), signals are not able to arrive at the receiver with perfect synchronization, which implies that the reception at UE is asynchronous. This paper presents an evaluation on asynchronous UE reception in multi-cell downlink joint transmission systems using our LTE-based CoMP simulator. Then, due to asynchronous reception, we propose an improved reception strategy to mitigate the interference which compensate for Rx timing difference on Joint transmission (JT) CoMP systems. Simulation results show that the per-subband global precoding scheme widely used in the CoMP system is considerably sensitive to asynchronous reception since the performance is dominated by the subcarrier used for precoding vector calculation. It is verified that our proposed solution is able to achieve significant improvements under asynchronous reception.
Study of Sentiment Classification for Chinese Microblog Based on Recurrent Neural Network
ZHANG Yangsen, JIANG Yuru, TONG Yixuan
2016, 25(4): 601-607.   doi: 10.1049/cje.2016.07.002
[Abstract](200) [PDF 583KB](1700)
The sentiment classification of Chinese Microblog is a meaningful topic. Many studies has been done based on the methods of rule and word-bag, and to understand the structure information of a sentence will be the next target. We proposed a sentiment classification method based on Recurrent neural network (RNN). We adopted the technology of distributed word representation to construct a vector for each word in a sentence; then train sentence vectors with fixed dimension for different length sentences with RNN, so that the sentence vectors contain both word semantic features and word sequence features; at last use softmax regression classifier in the output layer to predict each sentence's sentiment orientation. Experiment results revealed that our method can understand the structure information of negative sentence and double negative sentence and achieve better accuracy. The way of calculating sentence vector can help to learn the deep structure of sentence and will be valuable for different research area.
MIMO Scheduling Effectiveness Analysis for Bursty Data Service from View of QoE
CHEN Lei, JIANG Dingde, BAO Rong, XIONG Jiping, LIU Fuqiang, BEI Lulu
2017, 26(5): 1079-1085.   doi: 10.1049/cje.2017.07.018
[Abstract](83) [PDF 418KB](315)
In the user selection phrase of the conventional Multiple-input-multiple-output (MIMO) scheduling schemes, the frequent user exchange deteriorates the Quality of user experience (QoE) of the bursty data service. And the channel vector orthogonalization computation results in a high time cost. To address these problems, we propose an inertial scheduling policy to reduce the number of noneffective user exchange, and substitute self-organization policy for channel vector orthogonalization computation to reduce computational complexity. The relationship between the scheduling effectiveness and the inertia of objective function is observed in the simulation. The simulation results show that the inertial scheduling policy effectively reduce the number of potential noneffective scheduling which is inversely proportional to the Mean opinion score (MOS) that quantifies the QoE. Our proposed scheduling scheme provides significant improvement in QoE performance in the simulation. Although the proposed scheduling scheme does not consider the channel vector orthogonalization in the user selection phrase, its throughput approaches the level of the throughput-oriented scheme because of its selforganization scheduling policy.
Differential Fault Attack on Camellia
ZHOU Yongbin, WU Wenling, XU Nannan, FENG Dengguo
2009, 18(1): 13-19.  
[Abstract](717) [PDF 423KB](64)
Camellia is the final winner of 128-bit blockcipher in NESSIE project, and is also certified as the international IETF standard cipher for SSL/TLS cipher suites.In this study, we present an effcient differential fault attack on Camellia. Ideally, by using our techniques, on average, the complete key of Camellia-128 is recovered with64 faulty ciphertexts while the full keys of Camellia-192and Camellia-256 are retrieved with 96 faulty ciphertexts.Our attack is applicable to generic block ciphers with overall Fiestel structure using a SPN round function.All theseattacks have been successfully put into experimental simulations on a personal computer.
An Ultra Low Steady-State Current Power-on- Reset Circuit in 65nm CMOS Technology
SHAN Weiwei, WANG Xuexiang, LIU Xinning, SUN Huafang
2014, 23(4): 678-681.  
[Abstract](1024) [PDF 832KB](802)
A novel Power-on-reset (POR) circuit is proposed with ultra-low steady-state current consumption. A band-gap voltage comparator is used to generate a stable pull-up voltage. To eliminate the large current consumptions of the analog part, a power switch is adopted to cut the supply of band-gap voltage comparator, which gained ultra-low current consumption in steady-state after the POR rest process completed. The state of POR circuit is maintained through a state latch circuit. The whole circuit was designed and implemented in 65nm CMOS technology with an active area of 120μm*160μm. Experimental results show that it has a steady pull-up voltage of 0.69V and a brown-out voltage of 0.49V under a 1.2V supply voltage rising from 0V, plus its steady-state current is only 9nA. The proposed circuit is suitable to be integrated in system on chip to provide a reliable POR signal.
Face Liveness Detection Based on the Improved CNN with Context and Texture Information
GAO Chenqiang, LI Xindou, ZHOU Fengshun, MU Song
2019, 28(6): 1092-1098.   doi: 10.1049/cje.2019.07.012
[Abstract](726) [PDF 3162KB](80)
Face liveness detection, as a key module of real face recognition systems, is to distinguish a fake face from a real one. In this paper, we propose an improved Convolutional neural network (CNN) architecture with two bypass connections to simultaneously utilize low-level detailed information and high-level semantic information. Considering the importance of the texture information for describing face images, texture features are also adopted under the conventional recognition framework of Support vector machine (SVM). The improved CNN and the texture feature based SVM are fused. Context information which is usually neglected by existing methods is well utilized in this paper. Two widely used datasets are used to test the proposed method. Extensive experiments show that our method outperforms the state-of-the-art methods.
Identity Based Encryption and Biometric Authentication Scheme for Secure Data Access in Cloud Computing
CHENG Hongbing, RONG Chunming, TAN Zhenghua, ZENG Qingkai
2012, 21(2): 254-259.  
[Abstract](1186) [PDF 273KB](109)
Cloud computing will be a main information infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for cloud computing platform is a big challenge. In this paper, we propose a secure data access scheme based on identity-based encryption and biometric authentication for cloud computing. Firstly, we describe the security concern of cloud computing and then propose an integrated data access scheme for cloud computing, the procedure of the proposed scheme include parameter setup, key distribution, feature template creation, cloud data processing and secure data access control. Finally, we compare the proposed scheme with other schemes through comprehensive analysis and simulation. The results show that the proposed data access scheme is feasible and secure for cloud computing.
A Global K-modes Algorithm for Clustering Categorical Data
BAI Tian, C.A. Kulikowski, GONG Leiguang, YANG Bin, HUANG Lan, ZHOU Chunguang
2012, 21(3): 460-465.  
[Abstract](561) [PDF 334KB](81)
In this paper, a new Global k-modes (GKM) algorithm is proposed for clustering categorical data. The new method randomly selects a sufficiently large number of initial modes to account for the global distribution of the data set, and then progressively eliminates the redundant modes using an iterative optimization process with an elimination criterion function. Systematic experiments were carried out with data from the UCI Machine learning repository. The results and a comparative evaluation show a high performance and consistency of the proposed method, which achieves significant improvement compared to other well-known k-modes-type algorithms in terms of clustering accuracy.
Large Spaceborne Deployable Antennas (LSDAs)-A Comprehensive Summary
DUAN Baoyan
2020, 29(1): 1-15.   doi: 10.1049/cje.2019.09.001
[Abstract](625) [PDF 4261KB](238)
This paper provides a survey of research activities of Large spaceborne deployable antennas (LSDAs) in the past, present and future. Firstly, three main kinds of spaceborne antennas, such as solid reflector, inflatable reflector and mesh reflector, are issued by showing the strengths and weaknesses. Secondly, a detailed research situation of LSDAs with mesh is discussed, for majority of the in-orbit large diameter and high frequency antennas are made in this type of structures. Thirdly, new conception of antenna is proposed as it does have both advantages of large aperture (high gain) and high precision (high frequency). Fourthly, the design theory and approach of LSDAs are concerned. It includes thermal-electromechanical multidisciplinary optimization, shaped beam design technique, performance testing technology and evaluation method, passive intermodulation of mesh, and application of new materials. Finally, the ultra large spaceborne deployable antennas of the next generation are presented, such as the deployable frame and inflatable reflector antennas, space-assembled ultra large antennas, smart array antennas and so on.

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