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25 December 2020, Volume 41 Issue 12

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Papers

Study of a new code set in multi-rate CDMA VLC system

Jianping WANG, Danyang CHEN, Huimin LU, Jianli JIN, Lifang FENG

2020, 41(12):  1-7.  doi:10.11959/j.issn.1000?436X.2020178

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For the diverse traffic requirements of the wireless communication multiple access system and the characteristics of VLC, a new orthogonal variable spreading factor zero cross correlation (OVSF-ZCC) code set was proposed for multi-rate VLC code division multiple access (CDMA) system, which consisted of unipolar spreading sequences with variable lengths, and zero cross correlation properties.Assuming the radiation of LED light source was Lambert distribution, a multi-rate CDMA-VLC system with proposed code set was further presented.The effects of construction parameters, transmission rate and distance on system performance were evaluated.The results show that the new code set can effectively reduce multiple access interference (MAI), and support multiple transmission rate requirements of different users in multiple access systems.

ABAC access control policy generation technique based on deep learning

Aodi LIU, Xuehui DU, Na WANG, Rui QIAO

2020, 41(12):  8-20.  doi:10.11959/j.issn.1000-436X.2020212

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To solve the problem of automatic generation of access control policies, an access control policy generation framework based on deep learning was proposed.Access control policy based on attributes could be generated from natural language texts.This technology could significantly reduce the time cost of access control policy generation and provide effective support for the implementation of access control.The policy generation problem was decomposed into two core tasks, identification of access control policy sentence and access control attribute mining.Neural network models such as BiGRU-CNN-Attention and AM-BiLSTM-CRF were designed respectively to realize identification of access control policy sentence and access control attribute mining, so as to generate readable and executable access control policies.Experimental results show that the proposed method has better performance than the benchmark method.In particular, the average F1-score index can reach 0.941 in the identification task of access control policy sentence, which is 4.1% better than the current state-of-the-art method.

Social network link prediction method based on subgraph evolution and improved ant colony optimization algorithm

Qiuyang GU, Chunhua JU, Gongxing WU

2020, 41(12):  21-35.  doi:10.11959/j.issn.1000-436X.2020223

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Based on improved ant colony algorithm and subgraph evolution fusion, a new unsupervised social network link prediction method (SE-ACO) was proposed.First, the special subgraph was determined in the social network graph.Then the evolution of the subgraph was studied to predict the new links in the graph, and the special subgraph was located by the ant colony method.Finally, using different network topology environments and data sets to test the proposed method.Compared with other unsupervised social network prediction algorithms, the proposed SE-ACO method has the best evaluation results, shorter running time and the best effect on most data sets, which indicates that graph structure plays an important role in link prediction algorithm.

Security model without managers for blockchain trading system

Longxia HUANG, Liangmin WANG, Gongxuan ZHANG

2020, 41(12):  36-46.  doi:10.11959/j.issn.1000-436X.2020235

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In view of the abuse of power by managers in the traditional centralized trading system, a security model without managers for the blockchain-based trading system was proposed, which also solved the problems of unsafe endorsement, untimely trading, low auditing efficiency and dynamic inefficiency caused by the elimination of managers.The proposed security model realized decentralization based on the blockchain technology, by using homomorphic authentication-based public auditing to achieve the secure endorsement and key updating for non-manager groups and efficient verification for transaction information respectively, introducing the reputation-based incentive mechanism to ensure the timeliness of the transaction.Finally, the security and reliability of the proposed security model were demonstrated by security proof and performance analysis, and the communication and computing costs are both lower than IPANM.

Multi-label feature selection based on dynamic graph Laplacian

Yonghao LI, Liang HU, Ping ZHANG, Wanfu GAO

2020, 41(12):  47-59.  doi:10.11959/j.issn.1000-436X.2020244

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In view of the problems that graph-based multi-label feature selection methods ignore the dynamic change of graph Laplacian matrix, as well as such methods employ logical-value labels to guide feature selection process and loses label information, a multi-label feature selection method based on both dynamic graph Laplacian matrix and real-value labels was proposed.The robust low-dimensional space of feature matrix was used to construct a dynamic graph Laplacian matrix, and the robust low-dimensional space was used as the real-value label space.Furthermore, manifold and non-negative constraints were adopted to transform logical labels into real-valued labels to address the issues mentioned above.The proposed method was compared to three multi-label feature selection methods on nine multi-label benchmark data sets in experiments.The experimental results demonstrate that the proposed multi-label feature selection method can obtain the higher quality feature subset and achieve good classification performance.

Recognition of non-drilled polar codes based on soft decision

Zhaojun WU, Zhaogen ZHONG, Limin ZHANG, Bo DAN

2020, 41(12):  60-71.  doi:10.11959/j.issn.1000-436X.2020254

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In order to solve the problem of the blind recognition of polar codes, the theorem 1 and theorem 2 were proved firstly, which reflects the relationship between length and rate of actual polar codes, and then theorem 3 which could distinguish frozen bit and information bit positions was also proved.Based on these three theorems, the codewords matrixes and Kronecker matrixes were constructed by traversing the possible code length values.Then the information bits were traversed to detect the check relationship between the codewords and the suspected dual space.In order to detect the check relationship, log likelihood ratio was introduced, based on its characteristics and optimal criteria, the code rate and information bit positions were estimated.The simulation results show that the conclusions of the three theorems are consistent with the results.At the same time, the proposed algorithm has a strong error tolerance.Under 6.5 dB and code length of 1024, the rate of recognition can reach more than 98%.

Social media user geolocalization based on multiple mention relationships

Yaqiong QIAO, Xiangyang LUO, Jiangtao MA, Chenliang LI, Meng ZHANG, Ruixiang LI

2020, 41(12):  72-81.  doi:10.11959/j.issn.1000-436X.2020229

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Aiming at the problem that the existing joint user geolocalization methods based on social media text and social relationships do not sufficiently mine the location correlation between heterogeneous data in social media, a social media user geolocalization method based on multiple mention relationships was proposed.First, a heterogeneous network was constructed by comprehensively considering the mention relationship between users, the user's mention relationship with location indicative words, and the user's mention relationship with geographic nouns.Then, a network simplification strategy was proposed to construct a user-location heterogeneous network that connects users live nearby more closely based on the common mention relationship.After that, a biased random walk algorithm was proposed for the graph node sampling to fully explore the network structure and alleviate the sparsity problem of known locations.Finally, a neural network classifier based on a multilayer perceptron was used to infer the user's location.Experimental results on three representative Twitter data sets of GEOTEXT, TW-US and TW-WORLD show that the proposed method can significantly improve the user geolocalization accuracy.

Blockchain-based access control mechanism for data traceability

Rongna XIE, Hui LI, Guozhen SHI, Yunchuan GUO, Ming ZHANG, Xiuze DONG

2020, 41(12):  82-93.  doi:10.11959/j.issn.1000-436X.2020232

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To improve the transparency and traceability of access control, a blockchain-based access control mechanism for data traceability and provenance was proposed.The proposed access control policy was transferred to the smart contract and deployed on the blockchain, and the access authorization evaluation was realized by executing the smart contract deployed on the blockchain to ensure the decentralization, transparency and traceability of the access control process.The manner of combining off-chain and on-chain was adopted, the object was stored in off-chain data server, and the object index was generated by the object storage address and hash value, and deployed on the object blockchain.The log of object access authorization and access were recorded in the log blockchain, any misbehavior was immutably recorded.The security analysis show that, the proposed mechanism achieve the properties of decentralization, transparency and traceability while ensuring the privacy of data.

Research on microwave photonic channelization receiving technology based on dual coherent optical frequency comb

Bo CHEN, Yangyu FAN, Yongsheng GAO

2020, 41(12):  94-99.  doi:10.11959/j.issn.1000-436X.2020176

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In order to meet the future development needs of broadband communications, a microwave photonic channelization receiver based on dual coherent optical frequency comb (OFC) was proposed.The used optical frequency comb can be generated by only a dual parallel Mach-Zehnder modulator (DPMZM), which not only has high degree of flatness and out band rejection ratio, flexible and adjustable free spectrum range, but also effectively simplifies the complexity of the receiver.In the I/Q demodulation module, by the balanced detection method the second-order intermodulation distortion (IMD2) and direct current (DC) offset were effectively suppressed, and the dynamic range of the receiver was improved, at the same time, the electrical hybrid couple (EHC) and electric bandpass filter (EBPF) were used to solve the problem of image interference that is common in superheterodyne architectures.Finally it achieves channelized reception of 5 GHz bandwidth RF signals.

Design and implementation of high-speed scalar multiplier for multi-elliptic curve

Bin YU, Hai HUANG, Zhiwei LIU, Shilei ZHAO, Ning NA

2020, 41(12):  100-109.  doi:10.11959/j.issn.1000-436X.2020226

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Aiming at the problem that the existing scalar multiplier cannot be applied to multi-elliptic curve and the cost is expensive, a high-speed scalar multiplier was designed, applicable to two types of elliptic curves over prime fields.Firstly, in terms of the scalar multiplication, secp256r1 base points were processed with the comb algorithm, and the Shamir algorithm for ordinary points, and the Montgomery ladder algorithm for Curve25519.Secondly, the operation of point addition and point doubling was optimized, and the condition of Z=1 in point addition was simplified, thereby effectively reducing the number of calculation cycles.Lastly, a fast modular reduction algorithm of Curve25519 was designed for modular multiplication.Multiplexing was an important factor in the entire designing process.A 1022K equivalent gate was selected for the 55 nm CMOS process.This allowed ordinary point scalar multiplications performed on secp256r1 and Curve25519 respectively, calculating at the speeds of 153 000 times per second and 158 000 times per second, with the speed for secp256r1 1.9 times that of the existing designed one.

Simulation of transmission characteristics of oceanic wireless optical communication systems based on orbital angular momentum multiplexing with space-time coding

Xiaoli YIN, Tong ZHENG, Zhiwen SUN, Zhaoyuan ZHANG

2020, 41(12):  110-117.  doi:10.11959/j.issn.1000-436X.2020253

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In order to mitigate the crosstalk caused by oceanic turbulence in the underwater wireless orbital angular momentum multiplexing optical communication system, the application of space-time coding technology in the system was studied.Based on Rytov approximation, the covariance method and interpolation method were used to simulate correlated random phase screens and then the influence of time-varying oceanic turbulence channel on orbital angular momentum signal was studied.The transmission characteristics of orbital angular momentum multiplexing optical communication system with space-time coding was analyzed by simulation.The phase structure function of the time-varying phase screens and the detection probability distribution of the beam carrying the orbital angular momentum through the time-varying simulation channel were in line with theoretical expectations.The simulation results show that the space-time coding technology can effectively mitigate the influence of ocean turbulence on the system bit error rate.

Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network

Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

2020, 41(12):  118-127.  doi:10.11959/j.issn.1000-436X.2020230

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To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.

Efficient signcryption scheme based on Cocks’ identity cryptosystem

Changgen PENG, Xiaoyu ZHANG, Hongfa DING, Shanhui YANG

2020, 41(12):  128-138.  doi:10.11959/j.issn.1000-436X.2020214

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Most of the existing identity-based signcryption schemes are based on bilinear or multilinear pairing operations construction.To solve the problem of low efficiency caused by complex pair operation, a new efficient signcryption scheme based on the identity cryptosystem of Cocks was proposed.Firstly, the security model of the proposed scheme was formalized, and the definition of confidentiality and unforgeability was given.Secondly, the quadratic residue problem was used to realize the concrete construction of the proposed scheme, and the signature algorithm was designed in a logical step by combining Jacobi symbol operation.Finally, the security proofed that the scheme satisfied the confidentiality and unforgeability was given under the random prediction model.The efficiency analysis shows that compared with the existing identity-based signcryption scheme, the proposed scheme greatly improves the computing efficiency and has good characteristics of identity-based cryptosystem.

Cooperative spectrum sensing method and performance analysis based on similarity between evidences

Zhiguo SUN, Xinyue REN, Zengmao CHEN, Ming DIAO

2020, 41(12):  139-147.  doi:10.11959/j.issn.1000-436X.2020245

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The Dempster-Shafer(DS) evidence theory was applied to cooperative spectrum sensing and address the paradox of evidence in classical DS evidence theory, a new weighted distance measure based algorithm was proposed.Firstly, the evidences were extracted for each sensing user.Then, the weighted distance measure of extracted basic probability assignment data was adopted as the similarity between evidences of sensing users.Finally, the similarity of evidences was transformed into credibility, which was utilized as the weight to obtain the weighted average of basic probability assignment.In order to reduce the amount of data reported to the fusion center, the projection approximation method was employed to adjust the basic probability assignment.Both theoretical analysis and simulation results show that the proposed method can improve the detection performance of spectrum sensing while the paradox of evidence exists.Compared with traditional methods the cooperation overhead is reduced.

Energy-efficient resource allocation method in mobile edge network based on double deep Q-learning

Peng YU, Junye ZHANG, Wenjing LI, Fanqin ZHOU, Lei FENG, Shu FU, Xuesong QIU

2020, 41(12):  148-161.  doi:10.11959/j.issn.1000-436X.2020218

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To improve the system energy efficiency in mobile edge networks, a resource allocation method based on double deep Q-learning(DDQL) for integration of communication, computing, storage resources was proposed for the downlink communication process under the network architecture of multiple tasks, end devices, edge gateways and edge servers.A resource allocation model was constructed, which took the minimization of average energy consumption of tasks as the optimization goal and set the constraints of task delay limits and communication, computing, and storage resource limits.According to the model characteristics, a suitable resource allocation model and method based on DDQL framework was proposed to make intelligent allocation decisions for communication and computing resources and allocate storage resources on demand.Simulation results show that the proposed DDQL-based solution can effectively solve the multi-task resource allocation problem with good converge and low time complexity, and it reduces the average energy consumption of tasks by at least 5% compared with the solving methods based on random algorithm, greedy algorithm, particle swarm optimization algorithm and deep Q-learning while ensuring the quality of service.

Indoor positioning and orientating system based on visible light communication

Guowei YANG, Zhaobiao HUANG, Bing FAN, Xuefang ZHOU, Meihua BI

2020, 41(12):  162-170.  doi:10.11959/j.issn.1000-436X.2020217

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For the insufficient research on the simultaneously positioning and orientating system, a VLC positioning and orientating algorithm based on combining particle swarm optimization (PSO) and beetle antennae search (BAS) was proposed.The PSO algorithm was used to explore the optimal direction of the receiver and meanwhile the BAS algorithm was used to search the best three-dimensional coordinates of each particle in the current direction.Firstly, the indoor space of 3 m×3 m×5 m and the SNR of 40 dB were assumed in the simulation, the proposed VLC indoor positioning and orientating system could achieve the average positioning error of 4.82 cm and average orientating error of 2.24°.Then, in the laboratory space of 0.9 m×0.9 m×1.5 m, the experimental demonstration was accomplished for the first time, and the average positioning and orientating errors of this experimental system were 5.32 cm and 5.99°, respectively.Compared with the traditional VLC indoor positioning schemes, the proposed VLC positioning and orientating system does not need the prior knowledge of the height and direction of the receiver, which greatly reduces the system complexity and is applicable to a wider range of applications.

Bidirectional RNN-based private car trajectory reconstruction algorithm

Zhu XIAO, Xin QIAN, Hongbo JIANG, Chenglin CAI, Fanzi ZENG

2020, 41(12):  171-181.  doi:10.11959/j.issn.1000-436X.2020227

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To address the problem that in the complex urban environment, due to the inevitable interruption of GNSS positioning signal and the accumulation of errors during vehicle driving, the collected vehicle trajectory data was likely to be inaccurate and incomplete.a bidirectional weighted trajectory reconstruction algorithm was proposed based on RNN neural network.The GNSS-OBD trajectory acquisition device was used to collect vehicle trajectory information, and multi-source data fusion was adopted to achieve bidirectional weighted trajectory reconstruction.Furthermore, the neural arithmetic logic unit (NALU) was leveraged with the purpose of enhancing the extrapolation ability of deep network and ensuring the accuracy of trajectory reconstruction.For the evaluation, real-world experiments were conducted to evaluate the performance of the proposed method in comparison with existing methods.The root mean square error (RMSE) indicator shows the algorithm accuracy and the reconstructed trajectory is visually displayed through Google Earth.Experimental results validate the effectiveness and reliability of the proposed algorithm.

Correspondences

Research on berth occupancy prediction model based on attention mechanism

Zhurong WANG, Wei XUE, Yabang NIU, Ying’an CUI, Qindong SUN, Xinhong HEI

2020, 41(12):  182-192.  doi:10.11959/j.issn.1000-436X.2020241

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To solve the problem that the berth occupancy prediction accuracy decreases while the prediction step was increasing, a berth occupancy prediction model based on an attention mechanism was proposed, which was the multivariate time pattern information obtained by convolutional neural networks (CNN).The characteristic information was learned by the model training, and the sequence with higher correlation was assigned a larger learning weight, so that the highly correlated features output from the decoder could be used to predict the target sequence.Data sets of multiple parking lot were adopted to test the model.The test results show that the proposed model can estimate the real value well when the step length of berth occupancy prediction reaches 36.The prediction accuracy and stability of the model are improved compared with long short-term memory (LSTM) model.

Multi-attribute spectral clustering emergency detection based on word correlation feature

Weijin JIANG, Yang WANG, Xiaoliang LIU, Sijian LYU

2020, 41(12):  193-204.  doi:10.11959/j.issn.1000-436X.2020215

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For current methods for extracting emergencies had problems of low accuracy and low efficiency, an emergency detection method based on the characteristics of word correlation was proposed, which could quickly detect emergency events from the social network data stream, so that relevant decision makers could take timely and effective measures to deal with, making the negative impact of emergencies can be reduced as much as possible to maintain social stability.The simulation results show that the emergency event detection method has a better event detection effect in the real-time blog post data stream.Compared with the existing methods, the proposed method can meet the needs of emergency detection.Not only the detailed information of the sub-events can be detected, but also the related information of the events can be accurately detected.

Flow-of-traffic prediction program based mobile edge computing for Internet of vehicles using double auction

Yan LIN, Shuai YAN, Yijin ZHANG, Chunguo LI, Feng SHU

2020, 41(12):  205-214.  doi:10.11959/j.issn.1000-436X.2020252

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With an aim of maximizing the efficiency of edge offloading and the resource utilization of edge computing server simultaneously, a new flow-of-traffic prediction based edge computing offloading solution was proposed for Internet of vehicles (IoV).Firstly, both the efficiency utility function of vehicle and the resource utilization of mobile edge computing (MEC) server were established by considering task priority.Next, the formulated dual-objective optimization problem was transformed into a double auction problem between vehicles and MEC servers.Finally, based on the designed flow-of-traffic based pricing function of vehicle and MEC server, a McAfee auction algorithm was adopted to complete the edge computing process.Simulation results show that benefiting from the flow-of-traffic prediction information, the proposed solution can significantly improve both the efficiency of computation offloading and the utilization of computation resource.