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    Design and analysis of an improved OMU-NRDCSK communication system
    ZHANG Gang,LIU Jinhui,ZHANG Peng
    Journal of Xidian University    2020, 47 (4): 1-9.   DOI: 10.19665/j.issn1001-2400.2020.04.001
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    Aiming at the shortcomings of a low transmission rate in traditional Differential Chaos Shift Keying (DCSK) and a high bite error rate when transmitting multi-user information, an improved orthogonal multi-user noise reduction differential chaotic keying (OMU-NRDCSK) is proposed. The chaotic sequence generated at the sending end of the system is used as an information bearing signal after being duplicated, the multi-users’ information modulated by the Walsh codes are transmitted respectively through different delays. At the receiver, after passing through the moving average filter, the received signals are correlated with themselves to demodulate the initial information signals. The bit error rate formula for the system under the Rayleigh fading channel is derived and Monte Carlo simulation is carried out. Analytical and simulation results show that the OMU-NRDCSK system reduces the noise term variance by averaging the received signals and improves the bit error performance, with its transmission rate improved compared to the DCSK system, which effectively improves the bit error performance of the multi-user DCSK system.

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    Editorial:Introduction to the special issue on blockchain technology and its progress
    LI Jie,JIA Xiaohua,PEI Qingqi
    Journal of Xidian University    2020, 47 (5): 1-2.   DOI: 10.19665/j.issn1001-2400.2020.05.001
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    Improved face image classification method based on the local embedding network
    LIU Daohua,WANG Shasha,YANG Zhipeng,CUI Yushuang
    Journal of Xidian University    2020, 47 (4): 18-23.   DOI: 10.19665/j.issn1001-2400.2020.04.003
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    In order to improve the accuracy of facial expression recognition and face classification in a local linear embedding network, an improved face image classification method based on the local linear embedding network is proposed. Based on the local linear embedding algorithm, the intra-class to inter-class discrimination matrix is used as the input of the network. At the same time, the reconstruction of the face image set is used to improve the local linear embedding algorithm, and the improvement of the local linear embedding algorithm based on clustering is embedded into the construction process of the convolution kernel, thus increasing the discrimination degree of different types of faces. By the Extended Yale B data set and Olivetti Research Laboratory data set on the contrast experiment, the experiment is analyzed in the treatment of facial expressions and the effects of various methods in the face recognition task, the results show that, compared with the other methods, the recognition rate of the proposed improved locally linear embedding network face image classification method is raised by 11%~26%.

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    Blockchain radio access network:a new architecture for future mobile communications
    WANG Jiaheng,LE Yuwei,ZHANG Bowen,GUO Ruiwei,GAO Zheng,WANG Ziyue,LING Xintong
    Journal of Xidian University    2020, 47 (5): 3-10.   DOI: 10.19665/j.issn1001-2400.2020.05.002
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    With the rapid development of mobile communications and continuous network expansion, wireless resources become increasingly scarce. Based on the blockchain, the blockchain radio access network (B-RAN) has recently emerged as a promising architecture for the next generation mobile communication system. Via in-depth merging of blockchain and wireless communication technologies, the B-RAN presents a new paradigm to design future mobile networks. This paper briefly introduces the basic concept and workflow of the B-RAN, and provides several technical solutions for the B-RAN in order to satisfy different scenarios and needs. Furthermore, the security performance of the B-RAN is theoretically analyzed. This paper also designs a dedicated framework of the B-RAN and implements its core modules to test its practical performance. The test results show that the B-RAN has a noteworthy advantage in throughput under the scenario of multiple subnetworks. Compared with other blockchain architectures, the B-RAN has a significantly lower latency of service deployment and is able to achieve the balance dynamically between its security level and service latency.

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    Algorithm for recursive Bayesian localization triggered by temporalseries measurement information
    QIN Ningning,WANG Chao
    Journal of Xidian University    2020, 47 (4): 10-17.   DOI: 10.19665/j.issn1001-2400.2020.04.002
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    To improve the robustness of a position system and reduce the localization error, this paper proposes a fingerprint positioning method based on the recursive Bayesian. To solve the blindness and unreliability of the location fingerprint data in an offline phase, the fingerprint database based on the sample variance is developed to measure the confidence of sampling values and reduce the impact of environmental factors, improving the reliability for online localization. The proposed method provides the target position at the current moment by utilizing the Markov model that is established by the constraint relationship between moments in the source movement, which avoids the jump problem of the position estimation and poor robustness and improves the localization accuracy. Extensive experimental results demonstrate that the average localization error norm of the proposed algorithm is no more than 0.927m, indicating significantly lower errors than other traditional schemes (often by more than 30 percent).

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    Editorial:introduction to the special issue on network and information security research progress·commemoration of Mr. XIAO Guozhen
    HE Dake,SHEN Bazhong,XING Chaoping,FENG Dengguo,REN Jian,GU Dawu,HU Yupu,ZHANG Yuqing,ZHANG Weiguo
    Journal of Xidian University    2021, 48 (1): 1-6.   DOI: 10.19665/j.issn1001-2400.2021.01.001
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    Editorial:Introduction to the special issue on advances in radar technology
    LIU Hongwei,SHUI Penglang,KONG Lingjiang,WEI Yinsheng,LIU Yongxiang,WANG Yu,LI Gang,CHEN Bo
    Journal of Xidian University    2021, 48 (2): 1-6.   DOI: 10.19665/j.issn1001-2400.2021.02.001
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    Algorithm for foggy-image pedestrian and vehicle detection
    WANG Yudong,GUO Jichang,WANG Tianbao
    Journal of Xidian University    2020, 47 (4): 70-77.   DOI: 10.19665/j.issn1001-2400.2020.04.010
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    In order to improve the accuracy of the foggy-image pedestrian and vehicle detection, a novel and practical Foggy-image pedestrian and vehicle detection network (FPVDNet) based on the Faster R-CNN is proposed. First, a foggy-density discriminating module (FDM) is proposed to influence the density of the foggy images. In this way, the prediction from the FDM could determine the subsequent operations for different densities of the fog (No-fog, Light fog, and Dense fog). Then, the squeeze and excitation module (SE Module) is designed to use the attention mechanism to improve the feature extraction capability of the network. Meanwhile, the method of the deformable convolution network is applied to add offsets and learn the offsets from target tasks to enhance the transformation modeling capacity of CNNs. Finally, for lack of the annotated fog image dataset, it is necessary to generate a simulated fog image training dataset through the atmospheric scattering model. The simulated foggy image inherits the annotation of the clear image and increases the information on the fog density. Experiments by the proposed FPVDNet are carried out on the 1, 500 real-fog images and 500 real-clear images, with experimental results showing that, compared with the original Faster R-CNN, the mean average detection accuracies are improved 2%~4% by using the FPVDNet.

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    Datafusion method of multi-sensor target recognition in complex environment
    LU Liping,ZHANG Xiaoqian
    Journal of Xidian University    2020, 47 (4): 31-38.   DOI: 10.19665/j.issn1001-2400.2020.04.005
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    In the complex battlefield environment, the uncertainty of target information causes the target recognition difficulty and misjudgment, which brings about the problem of a low accuracy of target recognition results. This paper proposes a data fusion method for multi-sensor target recognition based on the discrete factor, which can give rise to the output data of the multi-sensor at the multi-period and multi-regions detection, and bring about the discrete factor of obtaining target characteristic corresponding sensors. It can provide the current weight of multi-sensor target recognition according to the discrete factor, establish the relative consistency and the relative weighted consistency function of multi-sensor target recognition, combine the current weight of multi-sensor target recognition and the related consistency function, and construct the data fusion result support calculation model of multi-sensor target recognition. Experimental results show that when the environment is complex, the data fusion method for multi-sensor target recognition based on the discrete factor has more accurate target recognition results, which conforms to the reality in comparison with the data fusion method for target recognition with a given sensor weight in advance. It is shown that the method proposed in this paper is more reliable and has a certain anti-interference ability.

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    Radar HRRP based few-shot target recognition with CNN-SSD
    GUO Zekun,TIAN Long,HAN Ning,WANG Penghui,LIU Hongwei,CHEN Bo
    Journal of Xidian University    2021, 48 (2): 7-14.   DOI: 10.19665/j.issn1001-2400.2021.02.002
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    The development of radar high resolution range profile(HRRP)non-cooperative targets recognition technology is mainly limited by two aspects:(1) Due to the low observation frequency of non-cooperative targets,the number of labeled HRRPs is insufficient,making non-cooperative HRRP based target recognition a typical few-shot recognition problem,which is still a hot and difficult issue without definite conclusion in the academia.(2) The existing HRRP based target recognition methods are mostly based on the hypothesis of complete dataset,making them mismatch with non-cooperative target recognition in few-shot setting.In this paper,we put aside the complete hypothesis and propose an HRRP based few-shot target recognition method with CNN-SSD.The proposed method first uses a complete training HRRP containing 45 classes of cooperative targets to learn an initial category-independent feature extractor,on the basis of which we further utilize the model sequential self-distillation mechanism to obtain a more generalized feature extractor.Finally,the generalization ability of the extracted features is evaluated on unseen non-cooperative targets during training.Experimental results on self-simulated HRRP dataset reveal that the proposed method can achieve an average recognition rates of 61.26%,84.69% and 92.52% respectively when only 1,5 and 10 annotated HRRPs of non-cooperative targets are available.

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    Scheme for miniature time difference measurement with a high resolution and a large range
    QU Bayi,LIU Yehao,ZHANG Taojing,LIU Wei,YU Dongsong,ZHOU Wei
    Journal of Xidian University    2020, 47 (4): 24-30.   DOI: 10.19665/j.issn1001-2400.2020.04.004
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    This paper presents some solutions to the problems in the precise time interval measuring instrument such as the contradiction between high resolution and wide measurement range, the high temperature sensitivity, the low reliability and the big volume and power consumption. The reference signal is used to generate calibration signals to automatically calibrate the analog circuits which are greatly affected by the temperature. The calibration data are used to amend the conversion coefficient between voltage and time interval and the temperature sensitivity of the instrument is greatly reduced. To avoid the gross error in the measurement result caused by the false trigger of the counter, the double counter synchronous measurement technique is adopted and the logic algorithm is used for analyzing and correcting the measured results. Electronic counting method and time-to-voltage converter method are combined together to meet the requirements of the measurement range and resolution of the instrument. The circuit board’s area of the prototype is only 10cm2. The prototype’s effective resolution is above 10ps and the standard deviation of multiple measurement results is below 15ps, the measurement range is wider than 20, 000 seconds, and its measurement results are highly reliable.

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    High performance multiply-accumulator for the convolutional neural networks accelerator
    KONG Xin,CHEN Gang,GONG Guoliang,LU Huaxiang,Mao Wenyu
    Journal of Xidian University    2020, 47 (4): 55-63.   DOI: 10.19665/j.issn1001-2400.2020.04.008
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    The multiply-accumulator (MAC) in existing convolutional neural network(CNN) accelerators generally have some problems, such as a large area, a high power consumption and a long critical path. Aiming at these problems, this paper presents a high-performance MAC based on transmission gates for CNN accelerators. This paper proposes a new data accumulation and compression structure suitable for the MAC, which reduces the hardware overhead. Moreover, we propose a new parallel adder architecture. Compared with the Brent Kung adder, the proposed adder reduces the number of gate delay stages and improves the calculation speed without causing an increase in hardware resources. In addition, we use the advantages of the transmission gate to optimize each unit circuit of the MAC. The 16-by-8 fixed-point high performance MAC based on the methods presented in this paper has a critical path delay of 1.173ns, a layout area of 9049.41μm2, and an average power consumption of 4.153mW at 800MHz under the SMIC 130nm tt corner. Compared with the traditional MAC, the speed is increased by 37.42%, the area is reduced by 47.84%, and the power consumption is reduced by56.77% under the same conditions.

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    Propositional projection temporal logic based distributed model checking method
    SHU Xinfeng,WANG Changtai,WANG Yan,ZHANG Lili
    Journal of Xidian University    2020, 47 (4): 39-47.   DOI: 10.19665/j.issn1001-2400.2020.04.006
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    To alleviate the state-explosion problem of model checking, a novel distributed model checking method based on the propositional projection temporal logic (PPTL). First, the property to be verified in the PPTL formula is transformed into an automaton with the technique of Labeled Normal Form Graph, which in turn is partitioned into multiple subautomata according to the strongly connected components. Then, each subautomaton and the system model in the Hierarchical Syntax Chart are delivered to the members of the verification server cluster, and model checking of the system is implemented in parallel with the on-the-fly technique on multiple computers. Experimental results indicate that, compared with the standalone model checking approach, the proposed method can not only significantly reduce the time consumption but also verify more complex systems.

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    Using Monero to realize covert communication
    LAN Yiqin,ZHANG Fangguo,TIAN Haibo
    Journal of Xidian University    2020, 47 (5): 19-27.   DOI: 10.19665/j.issn1001-2400.2020.05.004
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    The development of traffic analysis technology makes many covert communication methods based on the TCP/IP architecture face many threats. The subliminal channel is one that can realize covert communication by using cryptographic systems such as digital signatures and authentication. During the digital signature process, both parties of the communication can transmit secret information, and no one except the two parties knows the existence of the secret information. As a new generation technology, the blockchain adopts a distributed structure, and its openness, data tampering and security make it an effective carrier for constructing subliminal channels. This article introduces Monero, a new type of digital currency that uses blockchain technology, and constructs two subliminal channels in Monero. The first is based on the sharing of keys between signers and verifiers. The second does not share keys. Covert communication is achieved through these two subliminal channels.

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    Research on key technology of blockchain privacy protection and scalability
    WANG Hui,WANG Licheng,BAI Xue,LIU Qinghua,SHEN Xiaoying
    Journal of Xidian University    2020, 47 (5): 28-39.   DOI: 10.19665/j.issn1001-2400.2020.05.005
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    The blockchain has typical features such as decentralization of accounts, data irrevocability and transparency of information, which solves to a certain extent the collaboration and value flow between individuals who do not trust each other. However, the public verifiability of the blockchain poses security challenges for user privacy, while its performance issues, especially in terms of transaction throughput and scalability, also limit further development of blockchain technology. This paper researches and discusses the two major aspects of blockchain privacy protection and scaling technologies. First, it outlines the Bitcoin and ETH technologies in the blockchain and the comparison between them; then, it introduces several typical blockchain-oriented key technologies and development status of privacy protection such as ring signature, zero knowledge proof, secure multi-party computing, homomorphic commitment and subvector commitment. Similarly, the key technologies and case studies of blockchain scale-up are introduced from both up and down the chain to break through the two major bottlenecks in the development of blockchain privacy protection and scalability, so that the blockchain has a smart contract function, under the premise of protecting user privacy with high transaction throughput and scalability, to meet the actual needs of a wide range of fields such as finance, education, social management and industrial logistics, is the future direction of development of the blockchain.

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    On the significance and function of the Xiao-Massey theorem
    FENG Dengguo
    Journal of Xidian University    2021, 48 (1): 7-13.   DOI: 10.19665/j.issn1001-2400.2021.01.002
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    Divide-and-conquer correlation analysis is an important stream cipher analytical method,which is one of the analytical methods that must be defended when designing the stream cipher.The frequently-used defense strategy is to make the cryptographic function used in the stream cipher have a certain correlation immune order.This kind of cryptographic function is called the correlation immune function.The characterization of correlation immune functions is the theoretical basis for constructing and analyzing such functions.Professor G.Z.Xiao and Professor J.L.Massey first gave the characterization of the Walsh spectrum of correlation immune Boolean functions (called Xiao-Massey theorem),which opened up a new research direction for the study of stream ciphers.This paper mainly reviews the Xiao-Massey theorem,sketches the significance of the Xiao-Massey theorem,and explains the function of the Xiao-Massey theorem.

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    Preliminary research on the blockchain protocol in satellite broadcasting network environment
    ZHANG Yinghao,LIU Xiaofan
    Journal of Xidian University    2020, 47 (5): 11-18.   DOI: 10.19665/j.issn1001-2400.2020.05.003
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    Low throughput has been the biggest obstacle to large-scale blockchain applications. During the past few years, researchers have proposed various schemes for improving the systems’ throughput. However, due to the inherent inefficiency and defects of the Internet, especially in data broadcasting tasks, these efforts have all proved unsatisfactory. In this paper, we propose a novel blockchain protocol which utilizes the satellite broadcasting network instead of the traditional Internet for data broadcasting and consensus tasks. An automatic resumption mechanism is also proposed to solve the unique communication problems of satellite broadcasting. Simulation results show that the proposed algorithm has a lower communication cost and can greatly improve the throughput of the blockchain system. Theoretical estimation of a satellite broadcasting enabled blockchain system’s throughput is 6 000 000 TPS with a satellite bandwidth of 20 Gbps.

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    3D model recognition and segmentation based on multi-feature fusion
    DANG Jisheng,YANG Jun
    Journal of Xidian University    2020, 47 (4): 149-157.   DOI: 10.19665/j.issn1001-2400.2020.04.020
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    Current methods focusing on 3D model recognition and segmentation have to some extent ignored the relationship between the high-level global single-point features and the low-level local geometric features of those models, resulting in poor recognition results. A multi-feature fusion approach which takes into consideration the aforementioned ignored relationship is proposed. First, a global single-point network is established to extract the global single-point features with high-level semantic recognition ability by increasing both the width of convolution kernel and the depth of the network. Second, an attentional fusion layer is constructed to learn the implicit relationship between global single-point features and local geometric features to fully explore the fine-grained geometric features that can better represent model categories. Finally, the global single-point features and fine-grained geometric features are further fused to achieve the complementation of advantages and enhance the feature richness. Experimental verification is carried out on the 3D model recognition datasets ModelNet40, ModelNet10 and segmentation datasets ShapeNet Parts, S3DIS, vKITTI, respectively, and comparison with current mainstream recognition algorithms shows that the proposed algorithm not only has higher recognition and segmentation accuracy, but also has stronger robustness.

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    A new method for white-box implementation of CLEFIA algorithm
    YAO Si,CHEN Jie,GONG Yating,XU Dong
    Journal of Xidian University    2020, 47 (5): 150-158.   DOI: 10.19665/j.issn1001-2400.2020.05.020
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    Considering the shortcomings of the white-box CLEFIA algorithm (Su-white-box CLEFIA algorithm) implemented by Su Shuai et al with perturbations technology, the analytical method of Michiels et al can recover the master key in a time complexity of no more than 2.5×229. In order to ensure that the CLEFIA algorithm runs safely in a white-box attack context, a white-box implementation scheme (new white-box CLEFIA algorithm) based on the lookup table technology is proposed, which requires 36.034MB of memory space. The white-box diversity values corresponding to the two types of lookup tables in this scheme are 2829 and 2813, respectively, and the time complexity for the affine equivalent algorithm can reach O(276). This scheme can effectively resist code extraction attacks, key extraction attacks, attacks by Michiels et al and analysis by De Mulder.

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    Genomic data privacy-preserving scheme based on the improved PSI protocol
    TIAN Meijin,MA Jianfeng,LIU Zhiquan,FENG Bingwen,WEI Kaimin
    Journal of Xidian University    2020, 47 (4): 94-101.   DOI: 10.19665/j.issn1001-2400.2020.04.013
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    In order to solve the problem of privacy leakage in the sharing of genomic data, a genomic data privacy-preserving scheme based on the improved Private Set Intersection (PSI) computing protocol is presented, which leverages the Bloom Filter, Cuckoo Hash, and Random Oblivious Transfer (ROT) extension protocol to not only protect the genomic sequence information on the user when detecting a disease-causing gene but also judge whether he or she has some disease factors or not. Moreover, the correctness and security of the proposed scheme in the detection scenario of disease-causing genes are proved in the semi-honest security model. In addition, a series of experiments is conducted to verify the efficiency of the proposed scheme. The results reveal that the running time and communication overhead of the proposed scheme are much less than those of the existing PSI schemes.

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    Algorithm for encrypted search with forward secure updates and verification
    LI Han,ZHANG Chen,HUANG Hejiao,GUO Yu
    Journal of Xidian University    2020, 47 (5): 48-56.   DOI: 10.19665/j.issn1001-2400.2020.05.007
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    Recent advances in cloud computing are further pushing forward the development of the technique known as searchable encryption. However, existing encrypted search schemes mainly consider a centralized setting, where a search is conducted in a traditional client-server model. How to apply searchable encryption schemes to an untrusted distributed setting like the blockchain environment remains to be explored. Meanwhile, the advanced security property like forward security is posing new challenges that traditional technologies are no longer sufficient to cope with. In this work, we explore the potential of the blockchain technique and propose a novel dual index structure for forward-secure encrypted search with dynamic file updates. We show how to synthesize this design strategy in the context of blockchain-based storage systems and achieve both optimal search and update complexity. We also propose a verification scheme to verify the correctness of search results and customize an encrypted on-chain checklist to achieve strong data protection and lower the blockchain overhead. We implement the prototype on a Redis cluster and conduct performance evaluations on the Amazon Cloud. Extensive experiments demonstrate the security and efficiency of the design.

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    Transmission synthesis scheme for a multicast system with unknown locations of eavesdroppers
    GAO Jianbang,YUAN Zhaohui,ZHOU Jing
    Journal of Xidian University    2020, 47 (5): 144-149.   DOI: 10.19665/j.issn1001-2400.2020.05.019
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    In order to solve the problem of multicast wireless secure communication with unknown locations of the eavesdroppers, a secure communication synthesis scheme was proposed based on the frequency diverse arrays. By studying the frequency diverse arrays model and analyzing the beam pattern, a random frequency diverse array is constructed at the transmitter. At the same time, combined with the added artificial noise baseband signal processing method, the maximizing artificial noise energy method is designed to optimize the beamforming weighted vector of each multicast group, so as to improve the security performance of the multicast system. Numerical results show that the scheme realizes secure communication of a multicast system and can precisely control the signal energy received by legitimate users.

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    Polar coded non-orthogonal multiple access to 6G wireless systems
    NIU Kai,XU Wenjun,ZHANG Ping
    Journal of Xidian University    2020, 47 (6): 5-12.   DOI: 10.19665/j.issn1001-2400.2020.06.002
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    As the first type of channel codes which has achieved the channel capacity, polar codes are an important candidate for the 6G data transmission. A polar coded framework of the non-orthogonal multiple access (NOMA) to the 6G system is proposed. In this framework, the scheme for the polar coded coordinated NOMA is investigated to fulfill the requirement of high-capacity transmission of 6G systems. Furthermore, the scheme for the polar coded non-coordinated NOMA can achieve the ultra-high reliable access to the 6G internet scenario. All these schemes indicate that polar coded NOMA techniques can dramatically boost the performance of 6G wireless transmission and has a broad application prospect.

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    Blockchain privacy protection algorithm based on ring signature
    CHEN Siji,ZHAI Sheping,WANG Yijing
    Journal of Xidian University    2020, 47 (5): 86-93.   DOI: 10.19665/j.issn1001-2400.2020.05.012
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    Aiming at the problem of privacy protection when users transact or store data on the block chain, a ring signature algorithm which can be applied to a block chain system is proposed. First, the traditional ring signature algorithm is improved to generate keys based on the multi-PKG, which meets the requirements of the blockchain distributed trust environment. Second, different roles are assigned to the nodes in the block chain, and intelligent contract technology is used to control the generation and verification process of the signature. Finally, relevant experiments are carried out on the improved algorithm. Analysis and experimental results show that the algorithm proposed in this paper can protect the identity privacy of nodes in the block chain, has a good fault tolerance under the premise of ensuring efficiency, and can operate normally in the case of partial node failure.

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    Scheme for being able to regulate a digital currency with user privacy protection
    TIAN Haibo,LIN Huizhi,LUO Peiran,SU Yinxue
    Journal of Xidian University    2020, 47 (5): 40-47.   DOI: 10.19665/j.issn1001-2400.2020.05.006
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    The regulation of digital currency is currently a hot topic. At present, there are some digital currencies that protect user privacy well, but are unable to be regulated, which hinders the further application of these digital currencies. By taking Monero as an example, this paper proposes an improved solution based on a group signature and a knowledge proof for CryptoNote, the underlying technology of Monero, which can achieve the regulation of Monero. The group manager can trace a suspected transaction, determine the real identity of its sender, find the complete transaction list of the sender, and revoke the private key to freeze the coins of the sender when necessary.

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    Research and experiment on multi-user computational offloading based on mobile edge computing
    LU Jixiang,FANG Boya
    Journal of Xidian University    2020, 47 (4): 78-85.   DOI: 10.19665/j.issn1001-2400.2020.04.011
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    The fundamental problem of multi-user computation offloading for Mobile Edge Computing is investigated in heterogeneous overlay networks where each user can connect and offload its computing workloads to multiple heterogeneous wireless access points in parallel. The problem of average user overhead minimization with the delay constraint is formulated to obtain the optimal strategy of workload partition and heterogeneous resource allocation. A successive convex approximation (SCA) based algorithm is finally developed, which addresses the problem of non-convex optimization by iteratively solving a sequence of separable strongly convex problems. Numerical results are presented to prove that the proposed offloading mechanism can effectively reduce the service latency and energy consumption of users compared with the conventional non-cooperative approach.

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    Model predictive path integral method for nonlinear random vibration control
    GUO Kongming,JIANG Jun,XU Yalan
    Journal of Xidian University    2020, 47 (4): 48-54.   DOI: 10.19665/j.issn1001-2400.2020.04.007
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    In order to find a way to transfer back the state of a nonlinear random vibration system which is far away from the trivial equilibrium point, a model predictive path integral control method is introduced. Under certain conditions, the Hamilton-Jacobi-Bellman equation for optimal control of nonlinear random vibration can be linearized by exponential transformation. Based on the Feynman-Kac theorem, the path integral method can be used to solve the optimal control force. By introducing the idea of model predictive control, the control force can be updated in real time according to the actual state of the system. Numerical simulation is carried out for the control of two typical systems, van der Pol equation and Duffing equation. The results show that the state of the system can be quickly transferred to the vicinity of the ordinary equilibrium point, while the control force and real-time cost decreases monotonically after the initial fluctuation. Therefore, the model predictive control path integration method can be well applied to the vibration of random nonlinear systems far from the trivial equilibrium point.

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    Phased smoke detection algorithm using dual network fusion
    DU Lizhao,XU Yan,ZHANG Wei
    Journal of Xidian University    2020, 47 (4): 141-148.   DOI: 10.19665/j.issn1001-2400.2020.04.019
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    Existing video smoke detection methods have a low detection accuracy in complex scenes and cannot detect smoke areas in video frames accurately. In this paper, a phased smoke detection algorithm that combines the smoke movement process and the target detection algorithm is proposed. First, an improved ViBe algorithm based on smoke color features is used to extract the continuously moving smoke in video. Then, the YOLO v3 model is used as the target detection network. The channel attention mechanism is added to the residual structure of its backbone network. Focal-loss and GIoU are utilized to improve the loss function. According to the test of the smoke image data set, the detection time of the improved network on a single picture is 38.4ms and the mAP reaches 92.13%, which is 2.19% higher than that by the original model. While extracting smoke motion, the same frame is sent to the improved YOLO v3 for smoke detection. Finally, comprehensive discrimination is made based on the smoke detection results in stages. Public smoke video test results show that the algorithm has an average detection rate of 98.88%, which proves that the algorithm has a strong adaptability, a high detection efficiency in complex scenes and a high practical application value.

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    Editorial:Introduction to the special issue on information transmission and access technologies for B5G/6G
    BAI Baoming,MA Xiao,CHEN Wen,ZHANG Zhaoyang
    Journal of Xidian University    2020, 47 (6): 1-4.   DOI: 10.19665/j.issn1001-2400.2020.06.001
    Abstract138)   HTML29)    PDF(pc) (737KB)(94)       Save
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    GLMB extended target tracking based on one-step data association
    LI Cuiyun,LI Yang,JI Hongbing,SHI Renzheng
    Journal of Xidian University    2020, 47 (5): 137-143.   DOI: 10.19665/j.issn1001-2400.2020.05.018
    Abstract135)   HTML9)    PDF(pc) (2048KB)(37)       Save

    Due to the inseparability of measurements in neighborhood scenarios, the tracking performance of the traditional extended target tracking algorithm would degrade. In this paper, a new extended target tracking algorithm based on one step data association is proposed to solve the problem. First, the algorithm models the target with a multiplicative noise model. And then, the one step data association method in the Joint Probabilistic Data Association (JPDA) theory is combined with a Generalized Labeled Multi-Bernoulli (GLMB) filter. Simulation results show that the algorithm can track the target in cross and neighborhood scenarios effectively and that it is superior to the traditional extended target tracking algorithms based on measurement partition in estimation accuracy.

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    Knowledge-based adaptive detection of radar targets in sea clutter background
    XU Shuwen,WANG Zhexiang,SHUI Penglang
    Journal of Xidian University    2021, 48 (2): 15-26.   DOI: 10.19665/j.issn1001-2400.2021.02.003
    Abstract134)   HTML32)    PDF(pc) (3635KB)(82)       Save

    This paper focuses on the problem of radar targets detection in the compound-Gaussian sea clutter on the condition with the limited secondary data.The texture is modeled by the generalized inverse Gaussian distribution.Two adaptive detectors based on a priori knowledge of the speckle covariance matrix are proposed.First,the inverse complex Wishart distribution is exploited to model the speckle covariance matrix,and then an adaptive detector without using the secondary data is designed according to the generalized likelihood ratio.According to the maximum posterior test criterion,the secondary data are used to design an adaptive detector with secondary data and prior knowledge.Experimental results show that when the number of secondary cells is small,the two detectors proposed in this paper have a better detection performance than the GLRT-GIG detector.With different numbers of secondary cells,the proposed adaptive detector depending on the secondary data and a prior knowledge has the best performance.

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    Algorithm for detection of twice iterative signals for LTE-V2X systems
    LIAO Yong,SUN Ning,WANG Shuai,CHEN Ying
    Journal of Xidian University    2021, 48 (3): 1-8.   DOI: 10.19665/j.issn1001-2400.2021.03.001
    Abstract134)   HTML227)    PDF(pc) (986KB)(120)       Save

    Aiming at the traditional signal detection algorithms that cannot effectively deal with the inter carrier interference problem,this paper proposes an improved iterative parallel interference cancellation signal detection algorithm based on the Gauss Seidel algorithm.The proposed algorithm first uses the Gaussian Seidel algorithm with adaptive iterations to obtain the rough estimation of the signal to be detected,and then uses the iterative parallel interference cancellation algorithm to iteratively optimize the initial solution,and introduces the early update mechanism in the iterative process.Simulation results show that the detection performance of the proposed algorithm is better than that of the traditional iterative parallel interference cancellation algorithm in LTE-V2X communication systems,and approaches the performance of the optimal initial solution algorithm.The algorithm proposed in this paper achieves a better detection performance with a lower computational complexity,which provides a new idea for the design of the signal detection algorithm for LTE-V2X systems.

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    Fast design method for the high-performance dual-passband filter
    XU Tongtong,XIANG Zheng
    Journal of Xidian University    2020, 47 (5): 130-136.   DOI: 10.19665/j.issn1001-2400.2020.05.017
    Abstract131)   HTML18)    PDF(pc) (1930KB)(46)       Save

    In this paper, in order to improve the efficiency of designing the dual-passband filter, the extraction method of the coupling matrix of the dual-passband filter is studied based on the duplexer theory, and a dual-passband cavity filter is designed. First, the basic theory of the coupling matrix is analyzed, and then the method for extracting the coupling matrix based on the duplexer is studied. Finally, the corresponding coupling matrix is verified theoretically by the circuit model, and the design and simulation of the filter are performed using electromagnetic simulation software. The simulation results show that the dual-passband filter designed in this paper has the characteristics of a flexible and controllable passband, a low insertion loss, and good out-of-band rejection. The proposed method can improve the efficiency of designing the dual-passband filter.

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    Algorithm for the detection of a low complexity contrast enhanced image source
    WANG Junxiang,HUANG Lin,ZHANG Ying,NI Jiangqun,LIN Lang
    Journal of Xidian University    2021, 48 (1): 96-106.   DOI: 10.19665/j.issn1001-2400.2021.01.011
    Abstract130)   HTML13)    PDF(pc) (4033KB)(170)       Save

    With the rapid development of multimedia techniques,enhanced images,such as mobile phone pictures,are widely used due to its good visual quality,In general,conventional image enhancement algorithms include histogram equalization,gamma correction,and so on.Recently,a new reversible data hiding algorithm with the content enhancement function (denoted as RDH_CE) is proposed,which could achieve identical visual enhancement quality as conventional enhancement algorithms do when a certain amount of secret data is embedded.It is easy to have some security risk when one enhanced image with some suspicious code embedded in it is utilized.Therefore,an effective algorithm for identifying some suspicious RDH_CE and other regular ones (i.e.,histogram equalization and gamma correction) is proposed in this paper.By analyzing their implementation process,four features are designed and then SVM is employed to identify their source.Experimental results indicate that the proposed scheme can achieve a better performance compared with other state-of-art algorithms in terms of the accuracy and stability.

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    Survey of anonymous network applications and simulation platforms
    ZHENG Xianchun,LI Hui,WANG Rui,YAN Haonan,DAI Rui,XIAO Mingchi
    Journal of Xidian University    2021, 48 (1): 22-38.   DOI: 10.19665/j.issn1001-2400.2021.01.004
    Abstract123)   HTML20)    PDF(pc) (8010KB)(63)       Save

    An anonymous network can hide the real identities of and location information on users and service providers. With the expansion of cyberspace and the increasing importance of privacy protection,the research on anonymous networks has been further developed.For lack of application survey of anonymous networks at present,especially for lack of relevant reviews on the research on anonymous network simulation platforms,this paper,in the light of the current research status of anonymous networks,summarizes the existing privacy protection anonymous technology and the typical representatives of practical application of the anonymous network from multiple dimensions.We investigate the advantages and disadvantages of existing simulation platforms and environments and introduce the related works in terms of usability,efficiency,authenticity and the controllable scale.Finally,prospects for future research on anonymous network application are given to provide ideas for new research content and trends.

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    Mechanism for proof-of-reputation consensus for blockchain validator nodes
    LIU Naian,CHEN Zhihao,LIU Guokun,LI Yang
    Journal of Xidian University    2020, 47 (5): 57-62.   DOI: 10.19665/j.issn1001-2400.2020.05.008
    Abstract122)   HTML15)    PDF(pc) (772KB)(35)       Save

    A mechanism for proof-of-reputation consensus for blockchain validator nodes is proposed to deal with existing blockchain consensus mechanism's lack of evaluation of validator node's reputation and the inability to effectively prevent Byzantine behaviors. First, an interactive indicator is designed for validator nodes to represent their contribution in the blockchain network, which will be used as the reputation benchmark of validator nodes. Second, another reliability indicator is designed for validator nodes from the aspects of online time and the number of valid blocks, which will be used as the weight of the reputation improvement of validator nodes. Finally, the reputation of validator nodes of the current round is comprehensively calculated, and a set of producing validators of the current round is selected based on the reputation ranking. Experimental results show that the proof of reputation consensus mechanism has certain advantages in dealing with malicious and lazy behaviors, and that it can also reduce the impact of capital and energy consumption on the blockchain consensus mechanism while ensuring the validity of the credit evaluation.

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    Rule-based automatic program repair method
    HUANG Yuming,MA Jianfeng,LIU Zhiquan,FENG Bingwen,WEI Kaimin
    Journal of Xidian University    2020, 47 (4): 117-123.   DOI: 10.19665/j.issn1001-2400.2020.04.016
    Abstract122)   HTML10)    PDF(pc) (1299KB)(30)       Save

    To tackle the problem of a low accuracy of test suite-based automatic program repair methods, this paper proposes a rule-based automatic program repair method named RuleFix. The proposed method first mines implicit programming rules in programs to locate defects, and then selects an appropriate patch according to the implicit programming rules, and lastly verifies the patch by utilizing the program synthesis tool to ensure the correctness of the repair result. Moreover, to tackle the problem that the existing rule mining algorithms cannot effectively mine low-frequency rules, a low-frequency rule mining algorithm is proposed, which can derives new rules based on the existing rules to improve the ability of rule mining. Finally, a prototype tool is implemented based on the proposed method, and then the proposed method is compared with the existing automatic program repair methods. Experimental results demonstrate that the proposed method has a significantly higher repair rate and accuracy rate than the existing GenProg and PAR methods.

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    Research on the application of blockchain technology in the sharing of electronic medical records
    ZHAI Sheping,WANG Yijing,CHEN Siji
    Journal of Xidian University    2020, 47 (5): 103-112.   DOI: 10.19665/j.issn1001-2400.2020.05.014
    Abstract121)   HTML14)    PDF(pc) (1674KB)(27)       Save

    Electronic health records contain the occurrence, development and treatment of patients' diseases, and have a high medical value. Due to the privacy and sensitivity of medical data, data sharing and privacy protection are key issues for electronic medical records. Aiming at the characteristics of decentralization and tamper resistance of the blockchain, an electronic medical record sharing model based on the blockchain is proposed. First, a private chain and an alliance chain are built to store the encrypted electronic medical and electronic medical's security index records of users, respectively. Second, a combination of distributed key generation technology and a type and identity based proxy re-encryption scheme is proposed, and a multi-center scheme is designed as a data sharing protocol, which uses the entrusted-proof-of-rights-and-interests algorithm to select proxy nodes. Finally, an analysis and calculation of the proposed scheme and the existing scheme in various aspects such as tamper resistance and attack resistance are conducted. The result shows that the scheme consumes less energy in terms of communication overhead and computing power so that it can achieve the safe sharing of medical data effectively.

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    Progress of and some comments on the research of side-channel attack for cryptosystems
    GU Dawu,ZHANG Chi,LU Xiangjun
    Journal of Xidian University    2021, 48 (1): 14-21.   DOI: 10.19665/j.issn1001-2400.2021.01.003
    Abstract115)   HTML14)    PDF(pc) (1149KB)(80)       Save

    Side-channel attack is among the real threats to a cryptosystem in practice.By tracking its latest development,the main research directions including information pre-processing,non-profiled and profiled analysis are classified and demonstrated.The research key points of side-channel attack are summarized,in which the limitation of relying on artificial assumptions is pointed out to be as the principal issue of the state-of-the-art methods.Once the artificial assumptions deviate from the actual situation,the effect of side-channel attack will be seriously affected or weakened.A possible technical solution to ruling out this limitation is given,that is,to make use of what we call the zero-assumption (or weak assumption) method.The next-step research points under this assumption are listed briefly.

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    Covert data transmission mechanism based on dynamic label in blockchain
    SI Chengxiang,GAO Feng,ZHU Liehuang,GONG Guopeng,ZHANG Can,CHEN Zhuo,LI Ruiguang
    Journal of Xidian University    2020, 47 (5): 94-102.   DOI: 10.19665/j.issn1001-2400.2020.05.013
    Abstract114)   HTML7)    PDF(pc) (1704KB)(24)       Save

    The existing blockchain data covert transmission scheme is faced with the problems of poor concealment, small channel capacity and low efficiency. This paper designs a new model for separating the data embedding mechanism from the transaction filtering mechanism, and proposes a new filtering algorithm based on the address dynamic label. In this scheme,the HMAC algorithm is used to construct the special address label, so that the receiving party can effectively screen the special transaction carrying the concealed information from the massive data in the blockchain ledger, and realize the concealed data transmission in the open blockchain scenario. Simulation results show that the proposed scheme can realize the hidden transmission of data in the real bitcoin network. The concealment and efficiency of the scheme are better than those of the traditional scheme.

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    Overview of Sybil attacks and defenses in the distributed architecture
    XU Zhicheng,LI Xiang,MAO Jian,LIU Jianwei,ZHOU Zhihong
    Journal of Xidian University    2021, 48 (1): 39-49.   DOI: 10.19665/j.issn1001-2400.2021.01.005
    Abstract113)   HTML7)    PDF(pc) (1638KB)(35)       Save

    In recent years,the distributed architecture has been widely used in Internet information services.The distributed architecture usually relies on multiple independent nodes to deal with potential malicious threats.However,for lack of authentication between nodes and for the difficulty of recognizing the identity in the network and the relationship between nodes,it is vulnerable to multiple identity attacks,namely,the Sybil attacks,which destroy the trust relationship between nodes.In this paper,we analyze the Sybil attacks in the distributed architecture and their defense methods.First,we give a brief introduction to attack models of the Sybil attacks in different application scenarios.Then,we discuss common Sybil defenses in distributed architectures,and then emphasize two main Sybil defenses in the social network,a typical and popular distributed architecture.Finally,we prospect the trends of future research on the Sybil attack.

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    Residual attention mechanism for visual tracking
    CHENG Lei,WANG Yue,TIAN Chunna
    Journal of Xidian University    2020, 47 (6): 148-157.   DOI: 10.19665/j.issn1001-2400.2020.06.021
    Abstract112)   HTML14)    PDF(pc) (2819KB)(36)       Save

    In recent years, with the development of training data and hardware, a large number of tracking algorithms based on deep learning have been proposed. Compared with the traditional tracking algorithm, tracking algorithms based on deep learning have a great developing potential. However, the traditional convolutional neural network structure cannot effectively perform its powerful feature learning and representation abilities in a tracking task. In this paper, an improved feature extraction network is proposed for video target tracking. Based on the traditional feature extraction network, an attention mechanism and a feature fusion strategy in the form of residual network are introduced. At the same time, a loss function based on the regional overlap rate is introduced in the training stage of the network model, which makes the algorithm produce a better positioning effect. Experimental results show that the improved algorithm can track the target accurately for a long time. Besides, the method has a generalization ability, which can be used for reference for other tracking algorithms based on deep learning.

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    Study on the block withholding attack based on the evolutionary game
    CHENG Yukun,XU Zhiqi
    Journal of Xidian University    2020, 47 (5): 77-85.   DOI: 10.19665/j.issn1001-2400.2020.05.011
    Abstract108)   HTML8)    PDF(pc) (1505KB)(25)       Save

    The emergence of block withholding attack poses a threat to the security of the Bitcoin system and seriously damages the honest miners' right to obtain fair benefits. In this paper, we study this attack by building an evolutionary game model to reveal the dynamic evolution trend of players’ strategies and to deduce the evolutionary stability strategies with the help of replicator dynamics. We also analyze the strategy choices of miners under the different supervision and punishment measures of the pool and put forward corresponding suggestions for the pool. Finally, we conduct numerical simulation by Matlab to verify the effectiveness of our analysis by the evolutionary game model. The simulation results show that the mining pool can effectively mitigate the block withholding attack at a relatively low frequency of supervision and high penalty.

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    Optimization of the voltage regulators and voltage noise for the power delivery network
    WANG Lu,WANG Leilei
    Journal of Xidian University    2020, 47 (4): 124-131.   DOI: 10.19665/j.issn1001-2400.2020.04.017
    Abstract107)   HTML7)    PDF(pc) (1259KB)(23)       Save

    In order to reduce both the power loss of the switched capacitor converter integrated in the on-chip power delivery network and the voltage noise at the load, this paper proposes an optimization method to optimize the capacitance allocation between the flying capacitors of the switched-capacitor converter (SCCs) and the decoupling capacitors at the load. By formulating and solving the inequality-constrained nonlinear programming problem, the SCCs’ flying capacitance and decoupling capacitance can be optimally allocated and the sum of power loss and voltage noise is effectively reduced. Experimental results show that the joint optimization of the SCCs’ capacitance and decoupling capacitance can reduce the sum of power loss and voltage noise by about 11%~28%. For larger power deliver networks, this method can efficiently reduce the power loss and voltage noise.

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    Method for assessment of network security situation with deep learning
    YANG Hongyu,ZENG Renyun
    Journal of Xidian University    2021, 48 (1): 183-190.   DOI: 10.19665/j.issn1001-2400.2021.01.021
    Abstract107)   HTML16)    PDF(pc) (1584KB)(45)       Save

    The traditional methods for assessment of network security situation rely on manual label and evaluation.When faced with a large amount of data,there appearsome problems such as low efficiency and poor flexibility.First,we propose a Deep Autoencoder-Deep Neural Network (DAEDNN) model to identify all kinds of attacks on the network.Then,the Under-Over Sampling Weighted (UOSW) algorithm is designed to improve the detection rate of the model on categories with a few training samples.Finally,we conduct model testing and calculate the attack probability.Besides,we determine the impact score of each type of attack and calculate the network security situation value.Experimental results show that the precision and recall of the proposed model are better than those of the compared models,and that the proposed model has a better performance in accuracy and efficiency.

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    Propagation properties of a non-canonical vortex beam in a high numerical aperture system
    LI Jinhong,PANG Xiaoyan,FENG Chen
    Journal of Xidian University    2020, 47 (4): 102-108.   DOI: 10.19665/j.issn1001-2400.2020.04.014
    Abstract106)   HTML6)    PDF(pc) (2568KB)(26)       Save

    A non-canonical vortex is an optical helical phase structure with the same topological charge of a canonical vortex but different phase distributions. Based on the Richards&Wolf vectorial diffraction theory, the expression for the strongly focused, linearly polarized non-canonical vortex beam is derived, and its propagation properties are studied numerically in the focal region. It is that the transverse focal shift does not only occur in the strongly focused, off-axis (or on-axis) canonical vortex beams, but also can be seen in a strongly focused, non-canonical vortex beam. The transverse focal shift in these two fields have the same form, but the factors influencing them are quite different. It is also demonstrated that because of the transverse focal shift, if both the semi-aperture angle and the phase distribution factor meet a certain requirement, the total field intensity pattern in the focus region can rotate clockwise in the propagation direction, while the intensity maxima will also rotate 180° from the negative half space to the positive half space. The result will provide a new way for controlling the field distribution in structured fields, which may be applied in optical tweezers.

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    Multi-user computation offloading approach for mobile edge computing
    ZHANG Wenzhu,CAO Beibei,YU Jinghua
    Journal of Xidian University    2020, 47 (6): 131-138.   DOI: 10.19665/j.issn1001-2400.2020.06.019
    Abstract104)   HTML5)    PDF(pc) (1385KB)(25)       Save

    Computation offloading technology in Mobile Edge Computing (MEC) offloads resource-intensive applications on mobile user devices to edge servers. It can solve the deficiencies of mobile devices in terms of computing power, storage capacity, and energy efficiency. Orienting to the LTE, a multi-user computation offloading approach for MEC environment is proposed, which can jointly optimize mobile users’ delay and MEC servers’ resource allocation balance. First, a mobile edge computing system model is designed, on the basis of which an objective function for jointly optimizing the average computation offloading delay and resource allocation balance is constructed. And then with the goal of minimizing the offloading delay of mobile users and allocating MEC server resources in a balanced manner, the optimal solution is solved, and the computation offloading is implemented reasonably. Simulation results show that the approach can effectively reduce the average offloading delay of multi-users, and balance the workload of MEC servers at the same time.

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    Waveletdomain dilated network for fast low-dose CT image reconstruction
    LI Kunlun,ZHANG Lu,XU Hongke,SONG Huansheng
    Journal of Xidian University    2020, 47 (4): 86-93.   DOI: 10.19665/j.issn1001-2400.2020.04.012
    Abstract104)   HTML12)    PDF(pc) (2633KB)(21)       Save

    Low-dose CT has the advantages of low radiation and high efficiency, but the noise and artifacts with low-dose CT images reduce the reliability of diagnosis. In order to improve the quality of low-dose CT images, this paper attempts to enhance the visuals of reconstructed CT images in the wavelet domain, and improve the running speed by combining the multi-dilated convolution and subpixel, so that the model can be better deployed to the CT equipment. The data set of "2016 AAPM Low Dose CT image Challenge" is used to evaluate the proposed method. Experimental results show that the visuals of reconstructed CT images are better. Compared with RED-CNN, the average PSNR of the proposed method is improved by 0.1428dB (1mm) / 0.0939dB (3mm), and the running speed on the CPU and GPU is increased by more than 55% and 50%, respectively.

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    Recommendation of platoon members by combining the blockchain and vehicular social network
    ZHAO Zijun,YING Zuobin,YANG Zhao,LIU Ximeng,MA Jianfeng
    Journal of Xidian University    2020, 47 (5): 122-129.   DOI: 10.19665/j.issn1001-2400.2020.05.016
    Abstract103)   HTML14)    PDF(pc) (1084KB)(20)       Save

    Aiming at the problems of safety and privacy threats in establishing autonomous vehicle platoons in vehicle social networks, which would hinder the widespread adoption of platoons, a scheme for recommendation of autonomous vehicle platoon members by combining the blockchain and vehicle social networks is proposed. A series of security protocols to form a privacy platoon recommendation algorithm is first proposed. Second, the homomorphic encryption and secure multi-party computing are integrated to protect data security and reduce the risk of privacy leakage. Finally, the blockchain and vehicle social networks are combined to achieve efficient system operation. The proof of security shows that the proposed scheme meets the requirement of privacy protection. Besides, experimental results show that the cost of communication and that of calculation in the proposed scheme are both acceptable and reliable and effective for the formation of the platoon.

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    Method for hydrometeor classification based on MC-DTSVMs
    LI Hai,SHANG Jinlei,SUN Tingyi,FENG Qing,ZHUANG Zibo
    Journal of Xidian University    2020, 47 (4): 132-140.   DOI: 10.19665/j.issn1001-2400.2020.04.018
    Abstract100)   HTML6)    PDF(pc) (2172KB)(21)       Save

    In order to solve the problem of precipitation particle classification in the case of random missing of polarization parameter data of two-polarization meteorological radar, a method based on matrix completion(MC) and decision tree support vector machine multi-classifier(DTSVMs) is proposed. First, the polarization parameter data with random miss is reconstructed according to the matrix completion algorithm, and then the training data are used to learn the DTSVMs, and finally the precipitation particle classification of the reconstructed data is realized by using the DTSVMs with good learning. By processing the measured data and analyzing the results, it is proven that this method can effectively solve the precipitation particle classification problem in the case of random missing of polarization parameter data.

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