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25 July 2020, Volume 41 Issue 7
Topics: Mobile AI
Overview on intelligent wireless communication technology
Yingchang LIANG,Junjie TAN,Dusit Niyato
2020, 41(7):  1-17.  doi:10.11959/j.issn.1000-436x.2020145
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In recent years,artificial intelligence (AI) has been applied to wireless communications,in order to address the challenges introduced by data explosion and Internet of everything.Firstly,three core technologies of AI were introduced,including deep learning,deep reinforcement learning,and federated learning.Then,an overview of their applications on wireless communications was provided,from the aspects of wireless transmission,spectrum management,resource allocation,network access,network and system optimization.Based on the overview,the principle,applicability,design methodology,pros and cons on applying AI technologies to solve wireless communication problems were analyzed and summarized.Regarding the existed limitations,the future development trends and research directions on intelligent wireless communication technologies were pointed out,to hopefully provide useful help and reference for the future research in this field.

Survey on user’s mobility behavior modelling in urban environment
Fengli XU,Yong LI
2020, 41(7):  18-28.  doi:10.11959/j.issn.1000-436x.2020147
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Urban environment has become a typical scenario for areas of mobile communication,transportation scheduling,disease controlling and so on,and modelling user’s mobility behavior plays an important role in these key applications.The research development in this area was combed and summarized,which provided a literature review for related works.Firstly,the main challenges in urban mobility modelling were discussed as well as the corresponding key scientific problems,which included mobility data augmentation,urban structure-aware mobility behavior discovering,multi-scale mobility behavior prediction and mobility data privacy protection.Furthermore,according to these key scientific problems,the recent developments and up-to-date scientific output in this area were summarized,which paved the way for future research.

Deep and robust resource allocation for random access network based with imperfect CSI
Weihua WU,Guanhua CHAI,Qinghai YANG,Runzi LIU
2020, 41(7):  29-37.  doi:10.11959/j.issn.1000-436x.2020148
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A deep and robust resource allocation framework was proposed for the random access based wireless networks,where both the communication channel state information (C-CSI) and the interference channel state information (I-CSI) were uncertain.The proposed resource allocation framework considered the optimization objective of wireless networks as a learning problem and employs deep neural network (DNN) to approximate optimal resource allocation policy through unsupervised manner.By modeling the uncertainties of CSI as ellipsoid sets,two concatenated DNN units were proposed,where the first was uncertain CSI processing unit and the second was the power control unit.Then,an alternating iterative training algorithm was developed to jointly train the two concatenated DNN units.Finally,the simulations verify the effectiveness of the proposed robust leaning approach over the nonrobust one.

Distributed interference coordination based on multi-agent deep reinforcement learning
Tingting LIU,Yi’nan LUO,Chenyang YANG
2020, 41(7):  38-48.  doi:10.11959/j.issn.1000-436x.2020149
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A distributed interference coordination strategy based on multi-agent deep reinforcement learning was investigated to meet the requirements of file downloading traffic in interference networks.By the proposed strategy transmission scheme could be adjusted adaptively based on the interference environment and traffic requirements with limited amount of information exchanged among nodes.Simulation results show that the user satisfaction loss of the proposed strategy from the optimal strategy with perfect future information does not exceed 11% for arbitrary number of users and traffic requirements.

Performance analysis of covert wireless communication based on beam forming with noise uncertainty
Yuda LIN,Liang JIN,You ZHOU,Yangming LOU
2020, 41(7):  49-58.  doi:10.11959/j.issn.1000-436x.2020137
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In order to establish covert wireless communication in Rayleigh fading environment with noise uncertainty,a scheme of downlink covert wireless communication based on complex Gaussian random coding and beam forming was adopted,and more importantly,the performance of covert wireless communication was analysed.Firstly,the covert probability of communication was analyzed by using the hypothesis test theory.Secondly,the optimal detection threshold of the illegal detection party was given and proved,and the closed expressions of the average covert probability,connection interruption probability and covert throughput of the system were further obtained.Finally,by jointly designing the transmission power and target covert rate,the optimal goal of the maximum covert throughput of the system was achieved,and the corresponding algorithm based on step search was given.The simulation results show that the beam forming technology could provide some gain for covert wireless communication.Compared with the ideal case in which the legitimate receiver is not affected by the noise uncertainty,the covert throughput in non-ideal case is significantly reduced and almost not affected by the basic noise level of the environment.

Design of next generation high throughput satellite communication system based on beam-hopping
Chen ZHANG,Gengxin ZHANG,Xianyu WANG
2020, 41(7):  59-72.  doi:10.11959/j.issn.1000-436x.2020083
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Beam-hopping technology provides a basis for flexible allocation and efficient utilization of satellite resources,and it is considered as a key technology of the new generation of high-throughput satellite.With the goal of service-driven,efficient utilization of resources and on-demand coverage of hot spots area,from the aspects of system architecture,communication system,working mechanism,resource allocation method and beam-hopping pattern design,user access strategy,air interface protocol design and system workflow,a top-down feasibility and technical foundation was provided for the design of a new generation of high-throughput satellite communication system based on beam hopping.Finally,it meet the requirements of flexible and mobile information service for the space-earth integration network,as well as the demand of the space-based backbone network with high reliability and large capacity transmission.

Privacy-preserving real-time road conditions monitoring scheme based on intelligent traffic
Jiayin LI,Wenzhong GUO,Xiaoyan LI,Ximeng LIU
2020, 41(7):  73-83.  doi:10.11959/j.issn.1000-436x.2020110
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To alleviate the traffic pressure on roads,reduce the appearance of road congestion,and avoid the occurrence of traffic accidents,a privacy-preserving intelligent monitoring (PPIM) scheme based on intelligent traffic was proposed in combination with the safe and k-nearest neighbor (KNN) algorithm.To ensure the security of traffic data,the data content was randomly divided into independent parts via the secure multi-party computing strategy,and the data components were stored and encrypted separately by non-colluding multi-servers.To improve the accuracy of road condition monitoring,an improved KNN traffic monitoring algorithm was proposed.By virtue of the similarity calculation of data,the correlation value to measure the degree of traffic condition relationship between roads was obtained.And it was integrated with the KNN as the weight coefficient.To speed up the processing of dense data,a series of data security computing protocols were designed,and the data security processing was realized.In addition,real traffic data were used to verify the algorithm.The results show that the improved KNN algorithm is helpful to improve the accuracy of traffic monitoring.The analysis shows that the algorithm can not only guarantee the safety of data but improve the accuracy of traffic monitoring.

User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network
Yinghui YE,Liqin SHI,Guangyue LU
2020, 41(7):  84-94.  doi:10.11959/j.issn.1000-436x.2020133
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In order to address the unfair user-centric energy efficiency (EE) problem caused by channel difference in the backscatter-assisted wireless powered communication network,a resource allocation scheme was proposed.Firstly,a mixed integer nonconvex fractional programming problem was formulated to maximize the minimum user-centric EE,subject to the quality of service and energy-causality constraints.Based on the generalized fractional programming theory,the original problem was transformed into a mixed integer nonconvex subtraction problem.With the aid of the slack variable,the proof by contradiction,the auxiliary variable and the mixed integer nonconvex subtraction problem were further transformed into an equivalent convex problem.Finally,an iterative algorithm was proposed to obtain the optimal solutions.Computer simulations validated the quick convergence of the proposed iterative algorithm,and that the developed resource allocation scheme efficiently guarantees the fairness among users in terms of EE.

Method of ciphertext retrieval in mobile edge computing based on block segmentation
Na WANG,Kun ZHENG,Junsong FU,Jian LI
2020, 41(7):  95-102.  doi:10.11959/j.issn.1000-436x.2020142
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Aiming at the efficiency of cloud computing ciphertext retrieval scheme,a method of ciphertext retrieval in mobile edge computing based on block segmentations was proposed.Firstly,the edge server was introduced to calculate the document similarity score,thereby the computational cost of cloud server was reduced and the processing efficiency of cloud server was improved.Secondly,most keywords that are not related to the query were filtered out by a method of block segmentations based on the MRSE scheme,thereby the efficiency of calculating the document similarity score was improved.Theoretical analysis and experimental results show that the solution is safe under the known background threat model.Compared with the existing scheme,the proposed scheme has the same security and higher retrieval efficiency.

Novel adaptive generalized principal component analysis algorithm based on Hebbian rule
Yingbin GAO,Xiangyu KONG,Qiaohua CUI,Haidi DONG
2020, 41(7):  103-109.  doi:10.11959/j.issn.1000-436x.2020134
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In order to adaptively estimate the generalized principal component from input signals,a novel generalized principal component analysis algorithm was proposed based on the Hebbian linear neuron model.Since the autocorrelation matrices of the signals were estimated directly from the sampled data at the current time,the proposed algorithm had low computation complexity.Trough analyzing all of the equilibrium points by Lyapunov method,it is proven that if and only if the weight vector in the neuron had the same direction with the generalized principal component,the proposed algorithm attains the convergence status.Simulation results shows that compared with some same type algorithms,the proposed algorithm has faster convergence speed.

Passive forensic based on spatio-temporal localization of video object removal tampering
Linqiang CHEN,Quanxin YANG,Lifeng YUAN,Ye YAO,Zhen ZHANG,Guohua WU
2020, 41(7):  110-120.  doi:10.11959/j.issn.1000-436x.2020151
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To address the problem of identification of authenticity and integrity of video content and the location of video tampering area,a deep learning detection algorithm based on video noise flow was proposed.Firstly,based on SRM (spatial rich model) and C3D (3D convolution) neural network,a feature extractor,a frame discriminator and a RPN (region proposal network) based spatial locator were constructed.Secondly,the feature extractor was combined with the frame discriminator and the spatial locator respectively,and then two neural networks were built.Finally,two kinds of deep learning models were trained by the enhanced data,which were used to locate the tampered area in temporal domain and spatial domain respectively.The test results show that the accuracy of temporal-domain location is increased to 98.5%,and the average intersection over union of spatial localization and tamper area labeling is 49%,which can effectively locate the tamper area in temporal domain and spatial domain.

Optimum response scheme of intrusion detection based on information theory
Youliang TIAN,Yulong WU,Qiuxian LI
2020, 41(7):  121-130.  doi:10.11959/j.issn.1000-436x.2020111
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Intrusion detection system (IDS) often inevitably presents major security risks caused by FPs and FNs.However,at present,an effective solution has not been found.In order to solve this problem,an optimal response model of intrusion detection based on information theory was proposed.Firstly,the intruder and IDS in the process of intrusion detection were abstracted into random variables,and the attack and defense model of intruder and IDS was constructed according to the results of the confrontation.Secondly,the defense channel of IDS was designed according to the attack and defense model,then the correct detection of IDS was transformed into the problem of successful transmission of 1 bit information in defensive channel.Finally,the defensive capability of the system was measured by analyzing the channel capacity of the defensive channel,the maximum mutual information of the defensive channel was the defensive limit capability of the IDS,and the corresponding strategy distribution was the optimal response strategy of the defensive capability of the system.The experimental results show that the scheme can effectively reduce the loss caused by FPs and FNs.

Energy efficiency optimization algorithm for heterogeneous NOMA network based on imperfect CSI
Yongjun XU,Hao XIE,Qianbin CHEN,Jinzhao LIN,Qilie LIU
2020, 41(7):  131-140.  doi:10.11959/j.issn.1000-436x.2020101
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In order to improve the suppression capability of parametric perturbation and energy efficiency (EE) of heterogeneous networks (HetNets),a robust resource allocation algorithm was proposed to maximize system EE for reducing cross-tier interference power in non-orthogonal multiple access (NOMA) based HetNets.Firstly,the resource optimization problem was formulated as a mixed integer and nonlinear programming one under the constraints of the interference power of macrocell users,maximum transmit power of small cell base station (BS),resource block assignment and the quality of service (QoS) requirement of each small cell user.Then,based on ellipsoid bounded channel uncertainty models,the original problem was converted into the equivalent convex optimization problem by using the convex relaxation method,Dinkelbach method and the successive convex approximation (SCA) method.The analytical solutions were obtained by using the Lagrangian dual approach.Simulation results verifiy that the proposed algorithm had better EE and robustness by comparing it with the existing algorithm under perfect channel state information.

Research on intelligent computing offloading model based on reputation value in mobile edge computing
Jin QI,Hairong SUN,Kun GONG,Bin XU,Shunyi ZHANG,Yanfei SUN
2020, 41(7):  141-151.  doi:10.11959/j.issn.1000-436x.2020105
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Aiming at the problem of high-latency,high-energy-consumption,and low-reliability mobile caused by computing-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminals in the mobile edge computing environment,an offload decision-making model where delay and energy consumption were comprehensively included,and a computing resource game allocation model based on reputation that took into account was proposed,then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.Simulation results show that the proposed method can meet the service requirements of emerging intelligent applications for low latency,low energy consumption and high reliability,and effectively implement the overall optimized allocation of computing offload resources.

Routing optimization method based on GPCR for vehicular Ad Hoc network
Zhiru GU,Min LI,Yonghong LONG,Xiaohua SHU,Qing RONG
2020, 41(7):  152-164.  doi:10.11959/j.issn.1000-436x.2020144
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To improve the performance in sparse networks,local optimum,and routing loop in the greedy perimeter coordinator routing (GPCR) protocol,the weighted-GPCR (W-GPCR) protocol was proposed.The relationship between vehicle node routing and other parameters such as the Euclidean distance between node pairs,moving direction and density was profoundly analyzed,the composite parameter weighted model was established and the calculation method was designed for the existing routing problems,the weighted parameter ratio was selected adaptively in different scenarios,so as to obtain the optimal next-hop relay node.In order to verify the performance of the W-GPCR method,the proposed method was compared with the existing methods such as the traditional geographic perimeter stateless routing (GPSR) protocol,GPCR and so on,and the results show that the proposed method is superior to the package delivery ratio,end-to-end delay,and average hop count.

Interference avoidance strategy for ultra dense network with pilot reuse
2020, 41(7):  165-171.  doi:10.11959/j.issn.1000-436x.2020120
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In the ultra dense network (UDN),the pilot reuse scheme would produce significant interference,which will affect the accuracy of channel estimation.To solve this problem,an interference avoidance strategy for UDN with pilot reuse was proposed.An interference model of subcarriers for UDN was provided and the interference probability of subcarriers was derived.Then,based on the model,a pilot position selection model was proposed and an interference avoidance strategy for UDN with pilot reuse was provided.The simulation results show that compared with the traditional channel estimation algorithm,the channel estimation with proposed interference avoidance strategy can effectively avoid the interference and ensure the accuracy of channel estimation in UDN with pilot reuse.

Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction
Haifei SI,Xingliu HU,Zhen SHI,Shiyong LI
2020, 41(7):  172-185.  doi:10.11959/j.issn.1000-436x.2020138
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Aiming at the problem that in the current electromagnetic environment,the modulation method is complicated,the frequency-consuming equipment increases,the spectrum is congested,and the electromagnetic environment interference increases,the algorithm of OFDM signal detection and subcarrier identification in the background of non-cooperative communication were deeply studied.Using the different distribution states of OFDM signals and single carrier signals in the time domain,a joint characteristic parameter was proposed to solve the existence problem of OFDM in the received signal.For the phase shift and frequency offset problems caused by the channel transmission to the signal,by using the periodic stability the blind parameter estimation was performed to obtain the signal prior information.On the basis of the obtained signal prior information,a multi-level classification and recognition method for non-cooperative OFDM signal sub-carrier signals was proposed.Therefore,a model based on non-cooperative communication system OFDM signal detection and subcarrier modulation identification was designed,and finally modulation identification of unknown signals was completed.Simulation experiments show that in non-cooperative communication systems,OFDM signals and single-carrier signals can be accurately identified,and ideal modulation recognition effects can be achieved on empty subcarriers,QPSK,and 16QAM in the receiver OFDM signal subcarriers,overcoming the channel transmission band The problems of phase shift and frequency offset have improved the accuracy of modulation mode identification.

Evaluation of mimic defense strategy based on M-FlipIt game model
Shaohu DING,Ning QI,Yiwei GUO
2020, 41(7):  186-194.  doi:10.11959/j.issn.1000-436x.2020136
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To make up for the lack of security performance evaluation of the mimic defense systems in the advanced persistent threat scenarios an improved game model based on the FlipIt game theory model was proposed.The dynamic strategy of mimic defense under different heterogeneity conditions was evaluated,and a case study for the simulation analysis was conducted.The simulation results show that the rotation of indefinite period can make up for the lack of heterogeneity and maintain the higher game payoff of defenders.

Semantic segmentation of 3D point cloud based on contextual attention CNN
Jun YANG,Jisheng DANG
2020, 41(7):  195-203.  doi:10.11959/j.issn.1000-436x.2020128
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Aiming at the under-segmentation of 3D point cloud semantic segmentation caused by the lack of contextual fine-grained information of the point cloud,an algorithm based on contextual attention CNN was proposed for 3D point cloud semantic segmentation.Firstly,the fine-grained features in local area of the point cloud were mined through the attention coding mechanism.Secondly,the contextual features between multi-scale local areas were captured by the contextual recurrent neural network coding mechanism and compensated with the fine-grained local features.Finally,the multi-head mechanism was used to enhance the generalization ability of the network.Experiments show that the mIoU of the proposed algorithm on the three standard datasets of ShapeNet Parts,S3DIS and vKITTI are 85.4%,56.7% and 38.1% respectively,which has good segmentation performance and good generalization ability.

Global efficiency estimation method of complex network based on fractal property
Sheng ZHANG,Weikai DAI,Feng WU,Wenxiang LAN
2020, 41(7):  204-212.  doi:10.11959/j.issn.1000-436x.2020118
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A method of network efficiency estimation based on fractal property was proposed for solving the problems of high complexity and time-consuming calculation of efficiency in large scale networks.Considering the fractal properties of complex network topology,the relationship between network efficiency and node correlation sum was analyzed,and the global network efficiency was estimated by partial nodes.Besides,to rapidly find the fractal properties of complex networks,a fractal property discrimination method based on node correlation sum was proposed.The experimental analysis in the construction network and the real-world network show that the proposed method can accurately and effectively estimate the global efficiency of the network,which reduces the calculation time by at least 90% compared with the original method.

Research of authentication techniques for the Internet of things
Hongqiang YAN,Linjie WANG
2020, 41(7):  213-222.  doi:10.11959/j.issn.1000-436x.2020131
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Identity authentication technology is a key technology in the Internet of things (IoT)security field which ensures the authenticity of the identity information of users and device nodes connected to the IoT.Due to the low cost,low power consumption,small storage of IoT devices and heterogeneity of IoT network,the identity authentication mechanisms in traditional computer networks are often not applicable.Firstly,the development process of IoT was introduced,the security risks of IoT and the challenges faced by the authentication work were analyzed.Then the emphasis was put on comparison of the advantages and disadvantages among five typical authentication protocols.Moreover,the authentication technologies in several practical scenarios of RFID,smart grid,Internet of vehicles,and smart home were summarized and analyzed.Finally,the future research direction was discussed.

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Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Edited by: Editorial Board of Journal on Communications
Published by: Editorial Department of Journal on Communications
Address: F8, You Dian Publisher Building, No.1l, Chengshousi Road,Fengtai Distict, Beijing 100078, PR China
Chief Editor: ZHANG Ping
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Executive Director:ZHAO Li
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ISSN 1000-436X
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