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01 February 2019, Volume 40 Issue 2

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Topics:5G and AI

Research on crowd flows prediction model for 5G demand

Zheng HU,Hao YUAN,Xinning ZHU,Wanli NI

2019, 40(2):  1-10.  doi:10.11959/j.issn.1000-436x.2019042

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The deployment and planning for ultra-dense base stations,multidimensional resource management,and on-off switching in 5G networks rely on the accurate prediction of crowd flows in the specific areas.A deep spatial-temporal network for regional crowd flows prediction was proposed,by using the spatial-temporal data acquired from mobile networks.A deep learning based method was used to model the spatial-temporal dependencies with different scales.External factors were combined further to predict citywide crowd flows.Only data from local regions was applied to model the closeness of properties of the crowd flows,in order to reduce the requirements for transmitting the globe data in real time.It is of importance for improving the performance of 5G networks.The proposed model was evaluated based on call detail record data set.The experiment results show that the proposed model outperforms the other prediction models in term of the prediction precision.

Deep reinforcement learning based resource allocation algorithm in cellular networks

Xiaomin LIAO,Shaohu YAN,Jia SHI,Zhenyu TAN,Zhongling ZHAO,Zan LI

2019, 40(2):  11-18.  doi:10.11959/j.issn.1000-436x.2019002

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In order to solve multi-objective optimization problem,a resource allocation algorithm based on deep reinforcement learning in cellular networks was proposed.Firstly,deep neural network (DNN) was built to optimize the transmission rate of cellular system and to complete the forward transmission process of the algorithm.Then,the Q-learning mechanism was utilized to construct the error function,which used energy efficiency as the rewards.The gradient descent method was used to train the weights of DNN,and the reverse training process of the algorithm was completed.The simulation results show that the proposed algorithm can determine optimization extent of optimal resource allocation scheme with rapid convergence ability,it is obviously superior to the other algorithms in terms of transmission rate and system energy consumption optimization.

Deep learning based physical layer wireless communication techniques:opportunities and challenges

Guan GUI,Yu WANG,Hao HUANG

2019, 40(2):  19-23.  doi:10.11959/j.issn.1000-436x.2019043

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The development of the fifth-generation wireless communications (5G) system is promoted by the high requirements of the high reliability and super-high network capacity.However,existing communication techniques are hard to achieve the high requirements due to the more and more complexity design in 5G system.Currently,deep learning is considered one of effective tools to handle the physical layer wireless communications.Several potential applications based on deep learning were reviewed,and their effectiveness were confirmed.Finally,several potential techniques in deep learning based physical layer wireless communications were pointed out.

Latest progress on 3.5 GHz 5G NR trial

Guangyi LIU,Qixing WANG,Jianjun LIU,Fei WANG,Yi ZHENG

2019, 40(2):  24-30.  doi:10.11959/j.issn.1000-436x.2019045

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The 5^thgeneration mobile system (5G) was designed to fulfill the mobile market requirements for higher data rate,lower latency and higher connection density beyond 2020.3.5 GHz spectrum was a typical band for 5G deployment and could be a global band for 5G development.The performance of 3.5 GHz 5G would be very meaningful as a reference for global operators.Based on the first release of 5G specification frozen in June 2018 by 3^rdgeneration partner project (3GPP),field trials of 5G network in typical urban area were conducted to validate the peak data rate,cell throughput and latency of 5G network.The trial results show that 5G NR system can achieved 1 Gbit/s peak data rate and 4 ms latency of single direction.

Papers

Efficient privacy-preserving image retrieval scheme over outsourced data with multi-user

Xiangyu WANG,Jianfeng MA,Yinbin MIAO

2019, 40(2):  31-39.  doi:10.11959/j.issn.1000-436x.2019023

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The traditional privacy-preserving image retrieval schemes not only bring large computational and communication overhead,but also cannot protect the image and query privacy in multi-user scenarios.To solve above problems,an efficient privacy-preserving content-based image retrieval scheme was proposed in multi-user scenarios.The scheme used Euclidean distance comparison technique to rank the pictures according to similarity of picture feature vectors and return top-k returned.Meanwhile,the efficient key conversion protocol designed in proposed image retrieval scheme allowed each search user to generate queries based on his own private key so that he can retrieval encrypted images generated by different data owners.Strict security analysis shows that the user privacy and cloud data security can be well protected during the image retrieval process,and the performance analysis using real-world dataset shows that the proposed image retrieval scheme is efficient and feasible in practical applications.

Method of privacy protection based on multiple edge servers in personalized search

Qiang ZHANG,Guojun WANG,Shaobo ZHANG

2019, 40(2):  40-50.  doi:10.11959/j.issn.1000-436x.2019024

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In the plaintext environment,users' personalized search results can be obtained through users' interest model and query keywords.However,it may possibly result in the disclosure of sensitive data and privacy,which prevents using sensitive data in cloud search.Therefore,data is generally stored in the form of ciphertext in the cloud server.In the process of cloud search service,users intend to quickly obtain the desired search results from the vast amount of ciphertext.In order to solve the problem,it was proposed that a method of privacy protection based on multiple edge servers in personalized search shall be used.By introducing multiple edge servers and cutting the index as well as the query matrix,the computing relevance scores of partial query and partial file index are achieved on the edge server.The cloud server only needs to get the relevance score on the edge server and make a simple processing that can return to the most relevant Top K files by user query,so as to make it particularly suitable for a large number of users in the massive personalized ciphertext search.Security analysis and experimental results show that this method can effectively protect users’ privacy and data confidentiality.In addition,it can guarantee high efficiency in search to provide better personalized search experience.

SDN based network resource selection multi-objective optimization algorithm

Nan BAO,Jiakuo ZUO,Han HU,Xu BAO

2019, 40(2):  51-59.  doi:10.11959/j.issn.1000-436x.2019031

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For the problem of coexistence of different resource utility objectives and mutual influence of resource selection strategies in the complex structure of software-defined network (SDN),an SDN based network resource selection multi-objective optimization algorithm was proposed.The optimization goals of resource providers and clients were taken into account in the algorithm,and a resource selection multi-objective optimization model was constructed.The model was further solved by the reference vector based multi-objective optimization algorithm.Simulation results show that compared with other algorithms,the proposed algorithm could quickly converge to the uniformly distributed non-inferior solution set,and balance the optimization objects of multi-party in SDN based resource access management.

Amplitude information based robust tracking method for multiple marine targets

Chao LIU,Zhiguo ZHANG,Jinping SUN

2019, 40(2):  60-69.  doi:10.11959/j.issn.1000-436x.2019037

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A robust multi-Bernoulli filter based on the amplitude information of the target in sea clutter was proposed,in which the amplitude information of the target and sea clutter was exploited to improve the measurement likelihood.Therefore,the proposed approach could distinguish targets from clutter better when they were spatially close,which further enhanced the ability to track targets in marine radar detection applications.The simulation results of Swerling type Ⅰfluctuating targets tracking in K distributed sea clutter show that,the proposed algorithm is superior in performance to the robust multi-Bernoulli filter in terms of state estimation,cardinality estimation,as well as clutter rate estimation.

Opportunistic secure transmission scheme for simultaneous wireless information and power transfer

Keming MA,Yajun CHEN,Xin HU,Kaizhi HUANG,Xinsheng JI

2019, 40(2):  70-81.  doi:10.11959/j.issn.1000-436x.2019036

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Aiming at the different requirements of energy transmission and information transmission in simultaneous wireless information and power transfer (SWIPT),an opportunistic transmission scheme was proposed for enhancing physical layer security.Firstly,a SWIPT network with multi-cells was considered where multi-users,multi-eavesdroppers and the users were assumed to adopt time-switching based receivers and employ non-linear conversion model to harvest energy.The transmitter could dynamically switch between information transmission and power transfer according to the channel state,breaking the traditional fixed slot allocation scheme of energy transmission and information transmission.On this basis,the performances of energy transmission and information transmission were analyzed comprehensively,including the stability and efficiency of energy transmission,and the reliability and security of information transmission in the scenario of independent eavesdropping and joint eavesdropping.Next,a switching threshold optimization model was given to maximize its secrecy throughput under the constraint of the energy transmission,the reliability and secrecy performance requirements of information transmission.Finally,simulation results verify the validity of the proposed scheme.

Distributed congestion control strategy using network utility maximization theory in VANET

Guozhen TAN,Guodong HAN,Fuxin ZHANG,Nan DING,Mingjian LIU

2019, 40(2):  82-91.  doi:10.11959/j.issn.1000-436x.2019040

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Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.

Time delay estimation algorithm of narrow band internet of things based on inter-cell interference cancellation

Hong TANG,Hongyan MOU,Haolan YANG

2019, 40(2):  92-101.  doi:10.11959/j.issn.1000-436x.2019038

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Aiming at the characteristics of NB-IoT such as low power consumption,low cost and low sampling rate,an NB-IoT delay estimation algorithm based on inter-cell interference cancellation was proposed.To gradually eliminate the interaction between signals in each cell,an inter-cell iterative interference cancellation algorithm was considered.In each iteration,the idea of time-frequency cross-correlation overlapping was introduced on the basis of traditional correlation algorithms to break through the limitations of the sampling rate and further improve the accuracy of time delay estimation.At the same time,a first-arrival-path (FAP) searching algorithm based on noise threshold was used to suppress multipath effects.Through experimental simulation,the results show that the proposed algorithm can significantly improve the time delay estimation accuracy of NB-IoT on the basis of related algorithms.

Multi-point path planning based on the algorithm of colony-particle swarm optimization

Lijue LIU,Shuning LUO,Yan GAO,Meifei CHEN

2019, 40(2):  102-110.  doi:10.11959/j.issn.1000-436x.2019039

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The problem of multi-point path planning is a NP-hard problem,which is equivalent to finding the shortest path of a starting point and some specific node.Aiming at the problem of multi-point path planning,a retrospective ant colony-particle swarm optimization algorithm was proposed.This algorithm used Floyd-Warshall to transform the graph and combined ant colony algorithm and particle swarm algorithm to find the shortest path.The experimental results show that this algorithm can find the precise solution under small data,at the same time,under a large amount of data,can be better than the maximum minimum ant colony algorithm and genetic algorithm.

Underwater acoustic communication physical layer key generation scheme

Jingmei LIU,Zhiwei SHEN,Qingqing HAN,Jingwei LIU

2019, 40(2):  111-117.  doi:10.11959/j.issn.1000-436x.2019027

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To ensure the communication safety of unmanned underwater vehicle,a physical layer key generation scheme of underwater acoustic channel based on orthogonal frequency division multiplexing (OFDM) system was proposed.First,a local pilot assistance channel sounding protocol was proposed to solve the reciprocity impaired caused by the great propagation delay in the underwater acoustic channel,ensure high key randomness and enhance the defenses against nearby eavesdroppers.Secondly,double-layer compensation centralized combined with adaptive guard interval quantization method was proposed to improve key agreement rate and key generation rate.Simulation results show that the scheme effectively overcomes the problems of impaired reciprocity and ensures high key generation rate and high randomness on the premise that the key agreement is superior to the existing schemes.

Malicious PDF document detection based on mixed feature

Xuehui DU,Yangdong LIN,Yi SUN

2019, 40(2):  118-128.  doi:10.11959/j.issn.1000-436x.2019028

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Aiming at the problem of poor robustness and easy to evade detection in the detection of malicious PDF document,a malicious PDF document detection method based on mixed features was proposed.It adopted dynamic and static analysis technology to extract the regular information,structure information and API calling information from the document,and then a feature extraction method based on K-means clustering algorithm was designed to filter and select the key mixed features that characterize the document security.Ultimately,it improved the robustness of features.On this basis,it used random forest algorithm to construct classifier and perform experiment to discuss the detection performance of the scheme and its ability to resist mimicry attacks.

Performance analysis of two-way relay cooperation underlay cognitive radio networks based on WIPT

Jisheng XU,Fanzi ZENG,Kang LI,Yongfeng LI

2019, 40(2):  129-136.  doi:10.11959/j.issn.1000-436x.2019041

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The two-way relay cooperation for underlay cognitive radio networks based on WIPT was presented,where secondary system adopted the two-way relay cooperative transmission.First,the relay adopted a power splitting protocol to harvest energy and to decode information transmitted by secondary users,then the relay forwarded information to two secondary users by using the harvested energy.Subsequently the exact expression of the outage probability,the ergodic capacity and energy efficiency of the secondary user system were derived.Finally,numerical simulation discusses the impact on the system performance with regard to secondary transmission power.The results reveal that the two-way relay cooperation effectively reduces the outage probability of data transmission.The capacity and energy efficiency of the system reaches optimal level when the power allocation coefficient is 0.5.

Design of SCMA codebook based on chaotic signal and system performance analysis

Geng ZHAO,Yanyan MA,Yingjie MA

2019, 40(2):  137-144.  doi:10.11959/j.issn.1000-436x.2019026

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Sparse code multiple access (SCMA) technology is one of the multiple access technology schemes for the new generation of 5G.In order to solve the transmission requirement of massive users,the logistic chaos sequence was proposed instead of the random sequence in the original system to select the codeword.The constellation method based on trellis coded modulation (TCM) subset segmentation with the mapping matrix was used to generate codebook in the encoder,and decoded through message passing algorithm (MPA) detection method.The simulation results show that the bit error rate (BER) is low when the system uses the pseudo-random sequence of chaos to select the codeword,and the system also performs well under the condition of high overload rate.

Influence of nominal distortion of Beidou-3 B1C signal on ranging performance

Xue WANG,Yao GUO,Yongnan RAO,Xiaochun LU,Li KANG

2019, 40(2):  145-153.  doi:10.11959/j.issn.1000-436x.2019032

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The B1C signal is selected as a civil navigation signal for the BDS-3 system,which adopts a complex constant envelope modulation in the B1 frequency band.Therefore,it is easy to generate nominal distortion during signal generation.Such nominal distortion of each satellite produces inconsistent ranging deviation and directly degrades the system positioning performance.A complete ranging deviation estimation method was proposed for B1C signals in this paper.Firstly,the S-Curve Bias (SCB) was used to quantitatively analyze the B1C signal ranging deviation,and the standard correlation curve estimation method was proposed to realize the accurate estimation of the code phase deviation at the peak of the correlation curve.Secondly,a algorithm was designed to solve the problem of QMBOC signal mislocking at the platform during receiver tracking.Finally,the actual ranging bias and nature ranging bias of each satellite of Beidou-3 under different correlation intervals and front-end bandwidth of the user receiver were analyzed based on the satellite downlink signals collected from the 40-meter high-gain antenna at the National Time Service Center,and the recommended user receiver parameter range was given.The strategy proposed in this paper can be extended to other MBOC signal ranging error estimation,and the test results can be thought of as a reference to the development of BeiDou-3 receiver.

Comprehensive Review

Survey on trusted cloud platform technology

Xinfeng HE,Junfeng TIAN,Fanming LIU

2019, 40(2):  154-163.  doi:10.11959/j.issn.1000-436x.2019035

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Information security technology confronts severe challenges because of the safety demands of cloud computing.The trustworthiness and self-safety of cloud computing platform are the foundation of cloud computing security.The confidence of cloud users is the key issue the deep development and popularization for cloud computing.The trusted cloud computing technology provides a feasible solution.From the standpoint of guaranteeing the trustworthiness of cloud computing platform,related research progresses on trusted virtualization,construction of trusted cloud platform and trusted virtual machine were introduced.Additionally,the characteristics,application scopes and effectiveness of typical schemes were analyzed and compared.Finally,current limitations and possible directions for future research were discussed.

Correspondences

Integral fault analysis of the ARIA cipher

Yu SHEN,Wei LI,Dawu GU,Yixin WU,Shan CAO,Ya LIU,Zhiqiang LIU,Zhihong ZHOU

2019, 40(2):  164-173.  doi:10.11959/j.issn.1000-436x.2019033

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ARIA is a Korean standard block cipher,which is flexible to provide security for software and hardware implementation.Since its introduction,some research of fault analysis is devoted to attacking the last two rounds of ARIA.It is an open problem to know whether provoking faults at some former rounds of ARIA allowed recovering the secret key.An answer was given to solve this problem by showing a novel integral differential fault analysis on two rounds earlier of ARIA.The mathematical analysis and simulating experiments show that the attack can successfully recover its secret key by fault injections.The results in this study describe that the integral fault analysis is a strong threaten to the security of ARIA.The results are beneficial to the analysis of the same type of other block ciphers.

Single password authentication method for remote user based on mobile terminal assistance

Yuan XU,Chao YANG,Li YANG

2019, 40(2):  174-187.  doi:10.11959/j.issn.1000-436x.2019044

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To address the issue that users frequently reuse their weak passwords in password-based authentication system,single password authentication based on secret sharing between server and mobile terminal (SPASS) was proposed,which allows a remote user to use a single password to authenticate to multiple services securely and has no need to store any secret of the user in the client PC.Even when the mobile device is lost or stolen,no damage to the user’s information will be induced.Security analysis and performance test show that SPASS greatly improves the security of the user’s secret information and resists dictionary attacks,honeypot attacks,cross-site scripting attacks etc.Furthermore,the proposed scheme can lighten burden of the user’s memory,reduce the storage pressure and easy to be deployed.

Openstack authentication protocol based on digital certificate

Zhiqiang ZHU,Renhao LIN,Cuiyun HU

2019, 40(2):  188-196.  doi:10.11959/j.issn.1000-436x.2019030

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As the industry standard for open source cloud platforms,openstack uses the single-factor authentication method based on username and password that provides by keystone components to identity authentication mechanism,while it is not suitable for application scenarios with high security level requirements.A digital certificate-based identity authentication protocol which had cloud user identification protocol and authentication protocol was designed to meet the requirements.With expending the keystone component to achieve a digital certificate-based identity authentication system,a combination of authentication server,UKey technology,encryption technology and well-established key management and so on was used.According to the research,the system can effectively resist multiple cyber-attacks and improve the security of cloud users when they log in to the cloud platform.

k-error linear complexity of binary cyclotomic generators

Zhixiong CHEN,Chenhuang WU

2019, 40(2):  197-206.  doi:10.11959/j.issn.1000-436x.2019034

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In terms of the discrete Fourier transforms,the k-error linear complexities over F₂were discussed for Legendre,Ding-Helleseth-Lam,and Hall's sextic residue sequences of odd prime period p.More precisely,the 1-error linear complexities of these sequences were determined.Then,with some special restrictions of the order of 2 modulo p,partial results on their k-error linear complexities (k≥2) were proved.