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International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC

作者： Jun Liu Zhenming Lei Luyin Chen You Zhou Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China HAOHAN Data Technology Co. LTD

ISBN: (纸本)9781479986477

In the current highly competitive mobile phone market, understanding how users change their mobile phones is important for mobile network operators and phone manufactures, which is the focus of our study. In this paper, we analyze the user behavior of phone replacement from the perspective of users' economic conditions. We investigate and compare the migration of three major smartphone operating systems: iOS, Android and Windows Phone. In addition, we evaluate the customer loyalty of each operating system using the analytic hierarchy process (AHP) approach. This study is conducted based on the traffic data collected from a major cellular operator's network covering more than ten million users. The results demonstrate the relationships between users' phone replacement and economic conditions as well as the distinctions of customer loyalty among different operating systems.

关键词： Operating systems Economics Smart phones Mobile communication Monitoring Switches

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Research on WiFi User Dwell Time Distribution

Research on WiFi User Dwell Time Distribution

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Jie Meng Yihong Hu Guochu Shou Zhigang Guo Junfei Huang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Teleconnnunications Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Teleconnnunications Beijing China

ISBN: (纸本)9781467372121

In order to study the distribution law of human mobility time attribute and identify the individual identity according to the law, six months real data is collected in different scenarios through the Wireless-Data-Collection-Analysis-system developed by our laboratory. On the basis of AIC, we analyze the time distribution from the perspectives of wireless hotspot group users and individual users respectively. From the perspective of the group users, we verify that the users' daily cumulative dwell time meets the power-law distribution model. According to each user's average daily dwell time, we analyze the probability distribution of the average daily dwell time and conclude that it is consistent with the power-law with exponential cut off. From the angle of an individual user, we analyze the distribution of its daily dwell time in different time sections. The result shows that the daily dwell time probability distribution of the users who work on time is consistent with the multi-peak Gaussian distribution, and the moment of the highest peak point of different individuals are close. However, the distribution of the daily dwell time for those who do not need to work on time is related to the average daily dwell time. The shorter the average daily dwell time is, the better the distribution is in line with the long-tailed distribution.

关键词： Mobile communication Mathematical model Wireless communication Exponential distribution IEEE 802.11 Standard Mobile handsets Data models

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Improving high speed railway measured channel parameters centered at 2.6 GHz with the de-noise application based on wavelet transform

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Journal of Information and Computational Science 2014年第1期11卷 161-169页

作者： Yu, Deshui Xu, Chunxiu Zhao, Min Wang, Qian Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing 100876 China

In a wireless communication system for the high speed railway, system design engineers must have a thorough understanding of the radio-propagation characteristics, which is the essential aspect of wireless network designing and optimization. The channel impulse response can be generated by using slippage correlation measurement. Generally, the influence of the additive white Gaussian noise and the imperfect autocorrelation function is neglected, which will reduce the accuracy of the channel impulse response and the validity of the channel model. This paper proposes on a method which can eliminate the influence of the additive white Gaussian noise and the imperfect autocorrelation function through discrete wavelet transform. This method can provide a reliable guarantee to extract more accurate channel parameters, such as power delay profile, excess delay, and amplitude gain. And the results of simulation turn out that the de-noising method is effective. 1548-7741/Copyright © 2014 Binary Information Press.

关键词： Gaussian noise (electronic)

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User selection for cooperative spectrum sensing in mobile cognitive radios

User selection for cooperative spectrum sensing in mobile co...

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IEEE International Conference on Communications in China (ICCC)

作者： Meimei Duan Zhiming Zeng Caili Guo Fangfang Liu Beijing Key Laboratory of Network System Architecture Beijing University of Posts and Telecommunications Beijing China

Cooperative spectrum sensing is a key technique for cognitive mobile radio networks. User selection is vital to reduce overhead and to ensure high detection performance. In this paper, we proposed a user-selection algorithm based on stability and correlation of hybrid users, which provides high cooperative spectrum sensing performance by optimal users. Simulation and analysis results show that mobility increases spatial diversity and improves the detection performance within primary protected region (PPR). However, mobility degrades the detection performance when the users step out of the PPR. The proposed algorithm is suitable not only in mobile radios, but also in static radios networks.

关键词： Sensors Mobile communication Correlation Reliability Mobile computing Cognitive radio Algorithm design and analysis

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Interference of human's ankle to the channel characteristics of near surface WUSN

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The Journal of China Universities of Posts and Telecommunications 2014年第1期21卷 36-42页

作者： LI Li WU Wei CHEN Jian-ya LIU Yun-jie State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications

Because of its potential applications in agriculture, environment monitoring and so on, wireless underground sensor network（WUSN） has been researched more and more extensively in recent years. The main and most important difference of WUSN to terrestrial wireless sensor network（WSN） is the channel characteristics, which determines the design methodology of it. In this paper, the propagation character of electromagnetic（EM） wave in the near surface WUSN is analyzed, as well as the path loss model of it is given. In addition, the influence of human＇s ankle to the channel characteristics of near surface WUSN is investigated by electromagnetic theory analysis, simulation and experiment. A novel path loss model of near surface WUSN which takes the interference of human＇s ankle into consideration is proposed. It is verified that the existing of human above the WUSN system may cause additional attenuation to the signal of near surface WUSN which propagates as lateral wave along the ground. Moreover, the relation of the attenuation and operating frequency is deduced, which gives a reference to extend the frequency band applied in WUSN.

关键词： WUSN lateral wave human tissue path loss model EM wave attenuation

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Parametric channel modeling based OFDM channel estimation

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The Journal of China Universities of Posts and Telecommunications 2014年第5期21卷 1-8页

作者： QING Hao-bo LIU Yuan-an XIE Gang LIU Kai-ming LIU Fang Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications

A simplified parametric channel estimation approach was proposed for orthogonal frequency division multiplexing （OFDM） systems. Based on parametric channel model, this algorithm is composed of two parts： the estimation of channel parameters and channel interpolation. The exponentially embedded family （EEF） criterion is exploited to determine the number of channel paths as well as the multipath time delays. Consequently, the channel frequency responses is acquired via the estimated parameters. Additionally, the authors＇ scheme is computationally efficient owing to the needless of the eigenvalue decomposition or the estimation of signal parameters by the rotational invariance technique （ESPRIT）. Simulations are provided to validate the performance of this algorithm from perspectives of the probability of correct estimation and the mean square error （MSE）. It is demonstrated that this approach exhibits a superior performance over the existing algorithms.

关键词： channel estimation OFDM mean square error EEF criterion

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Two dimensional cooperation prediction algorithm of communication network traffic in smart grid

Two dimensional cooperation prediction algorithm of communic...

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International Conference on Communications and networking in China (CHINACOM)

作者： Huan Luo Tiankui Zhang Yong Sun Chunyan Feng Weidong Feng Beijing Key Laboratory of Network System Architecture and Convergence SICE Beijing University of Posts and Telecommunications Beijing State Grid Hubei Electric Power Company 430000 China

ISBN: (纸本)9781479987962

With the evolution from traditional power grid to smart grid, the network traffic has become much larger in the integrated services network of the smart grid. It is necessary to predict these network traffic and make early analysis warning to ensure the performance of the integrated services network. The existing algorithms show large prediction error in the several consecutive points after the turning point, which is called one step lag problem. In this paper, a two dimensional cooperation prediction algorithm is proposed to solve the one step lag problem by combining the advantages of two dimensions. The proposed algorithm uses the Autoregressive Integrated Moving Average Model as the vertical dimension prediction algorithm to capture the daily periodicity of the integrated services network's network traffic, and uses the wavelet neural network model as the horizontal dimension prediction algorithm to capture the unique trends of the forecast day. Simulation results show that the proposed algorithm solved the one step problem and significantly improved the prediction accuracy.

关键词： Prediction algorithms Predictive models Telecommunication traffic Neural networks Smart grids Algorithm design and analysis Intserv networks

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Dynamic recovery for survivable virtual network embedding

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The Journal of China Universities of Posts and Telecommunications 2014年第3期21卷 77-84页

作者： LU Bo HUANG Tao SUN Xiao-chuan CHEN Jian-ya LIU Yun-jie Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications School of Information Engineering Hebei United University

network virtualization is a promising way to overcome the current ossification of the Intemet. It is essential challenge to find effective, efficient and robust embedding algorithms for recovering virtual network. The virtual network mapping algorithm based on integer programming which was proposed months ago. But it did consider the faults of physical network resources, which is so called survivable virtual network embedding （VNE） problem. Previous strategies for enabling survivability in network virtualization focused on providing protection for the physical network or enhancing the virtual networks by providing backup physical resources in advance, and treated all the physical failures as link failures. In the article, a dynamic recovery method is proposed to solve the survivable virtual network embedding problem based on the integer programming VNE algorithm. The dynamic recovery method doesn＇t need to backup physical resources and it makes more substrate resources which can be used in the embedding. The dynamic recovery process will be activated only when physical failures occur. Different algorithms are used to recovery node and link failures. Simulations show that the method helps to recover almost all of physical failures by finding the substitute nodes and paths, and its performance is very close to that of pure VNE method without considering physical failures.

关键词： network virtualization integer programming survivable virtual network embedding dynamic recovery

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Global and individual mobility pattern discovery based on hotspots

Global and individual mobility pattern discovery based on ho...

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IEEE International Conference on Communications (ICC)

作者： Jie Yang Xinyu Zhang Yuanyuan Qiao Zubair Fadlullah Nei Kato Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Graduate School of Information Sciences Tohoku University Sendai Japan

Data collected from the mobile Internet have the potential knowledge to provide important human mobility patterns. Understanding human mobility patterns is important to many location-based services, and could be used to predict users' behavior. In this paper, we concentrate on the issue of discovering human mobility patterns on both global and individual levels based on hotspots. We study the human mobility trajectories during 22 days for 3474 individuals collected at the core of a metropolitan Long Term Evolution (LTE) network in China. We employ a parameter-free method to detect hotspots, and demonstrate the effectiveness of our mobility pattern discovery algorithm by using the hotspots identified on both global and individual levels. We analyze the occurrence time distribution of these patterns and find that the global mobility patterns have higher occurrence probability in the morning, which indicates that people in a city tend to share the common commuting routes. For individual mobility patterns, there exists a strong spatiotemporal correlation property, implying that the individual mobility patterns have their own typical occurrence time depending on the pattern's context.

关键词： Trajectory Mobile communication Transportation Mobile computing Cities and towns Next generation networking Long Term Evolution

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Characterizing and modeling of large-scale traffic in mobile network

Characterizing and modeling of large-scale traffic in mobile...

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IEEE Conference on Wireless Communications and networking

作者： Jie Yang Weicheng Li Yuanyuan Qiao Zubair Md. Fadlullah Nei Kato Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Graduate School of Information Sciences Tohoku University Sendai Japan

ISBN: (纸本)9781479984077

Recently, mobile Internet gained a strong momentum of development, which has led to increasing demand on mobile network traffic characterization and modeling. A good model of mobile network traffic can be used to make accurate prediction regarding various performance metrics. Based on the network trace collected from network backbone, our paper studies mobile network traffic characteristics in terms of the flow arrival numbers and flow connection duration. Basically, we employ the Poisson regression from Generalized Linear Model with time window clustering so as to approximate a time-dependent Poisson Process to the flow arrival process. Our analytical results demonstrate the accuracy of the adopted approach. In addition, through approximating the Phase Type distribution to the heavy-tailed distribution, our paper also models the flow connection duration. The obtained results can help us get a comprehensive understanding of the network performance, in accordance with which the resource usage may be optimized, e.g., we can expand network bandwidth or increase the buffer size when the network arrival is high.

关键词： Mobile communication Mobile computing Internet Measurement Conferences Monitoring Distribution functions

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