China Mobile Communications Corporation Research Articles

The spatiotemporal prediction method of urban population density distribution through behaviour environment interaction agent model

Based on the interrelationship between the built environment and spatial–temporal distribution of population density, this paper proposes a method to predict the spatial–temporal distribution of urban population density using the depth residual network model (ResNet) of neural network. This study used the time-sharing data of mobile phone users provided by the China Mobile Communications Corporation to predict the time–space sequence of the steady-state distribution of population density. Firstly, 40 prediction databases were constructed according to the characteristics of built environment and the spatial–temporal distribution of population density. Thereafter, the depth residual model ResNet was used as the basic framework to construct the behaviour–environment agent model (BEM) for model training and prediction. Finally, the average percentage error index was used to evaluate the prediction results. The results revealed that the accuracy rate of prediction results reached 76.92% in the central urban area of the verification case. The proposed method can be applied to prevent urban public safety incidents and alleviate pandemics. Moreover, this method can be practically applied to enable the construction of a “smart city” for improving the efficient allocation of urban resources and traffic mobility.

Impact of Reducing Data Plan Costs on the Digital Divide in China: A Digital Lifestyles Perspective

The digital divide first emerged as an important social and human rights issue in the 1990s. With the rapid development of wireless network technology (e.g., Wi-Fi and cellular networks) and mobile terminal devices (e.g., mobile phones, laptops, and tablets), this issue has shifted to concern mobile Internet access. The three main Chinese telecom operators (China Mobile Communications Corporation, China Unicom Communications Corporation, and China Telecom Communications Corporation) have recently promoted unlimited data plans (UDPs) to reduce information usage costs and increase mobile data use. However, assessments of the impact of these policy changes on the mobile digital divide are limited. This study therefore offers insights into how a reduction in information costs can eliminate this divide. Using a difference-in-differences (DID) approach based on a monthly panel of system-generated mobile app data for subscribers, we find that the UDPs have various effects on promoting the use of mobile Internet and on the digital divide, depending on whether subscribers are of high or low socioeconomic status (i.e., urban versus rural and rich versus poor). We show that the relative differences are alleviated, but the absolute difference further increases after the implementation of a UDP subscription. In addition, a UDP subscription has heterogeneous effects on lifestyles. For the poor or those in rural areas, only promoting UDP does not effectively narrow the mobile digital divide because of insufficient cognition about and persistent weaknesses in the use of information technology.

Design and implementation of intelligent environment monitoring system based on OneNET platform

With the development of electronic technology, remote monitoring has become the main development direction of data management. The monitoring of indoor environmental data is our main research content. The OneNET platform provided by China mobile communications corporation is used as the coordination command center of the intelligent monitoring application system for terminal design and development. OneNET platform provides standardized access terminal and the background monitor template type design method of the staff through constructing a set of environmental data acquisition and monitoring system based on OneNET, implementation of indoor environment parameters, such as temperature, temperature and concentration of PM2.5 real-time reporting and management operation, with abnormal data of automatic alarm. The system shows that the design based on the open platform can effectively improve the generation efficiency of new business and promote the development of Internet of things business.

Wristwatch-Style Wearable Dielectric Resonator Antennas for Applications on Limps

A wristwatch-style wearable dielectric resonator antenna (DRA) is proposed for the 2.45-GHz ISM band and sub-6 GHz 5G NR bands around 2.5 GHz, such as the commercial band for China Mobile Communications Corporation. The antenna is designed for applications on forearms and ankles. Practical concerns, including the aligning method, platform size, specific absorption rate, and user effects are investigated. Coplanar feeding structure is applied for alignment and isolation. Analysis of the watchband-like substrate is highlighted to avoid performance degradation. Given that platform configurations are not discretionary in actual devices, parasitic loading is introduced to attain desirable substrate effects and suppress unwanted ones. The user-device interplay is studied in light of actual application scenarios. The specific absorption rate is calculated through multilayer biological tissue models. Meanwhile, radiation variation caused by users is estimated based on human phantom models and measurements.

The Application Research on Busy-Time Traffic Prediction Based ESNs of Multivariate Principal Components Analysis

As single variable cannot provide comprehensive forecast information, Combining with the communication traffic data come from Xinjiang branch of china mobile communication corporation, the traffic and the four variables highly related with the traffic are done principal component analysis, the first principal component and the second principal component that they are obtained by principal components analysis (PCA) and dimension reduction are as input variables of ESNs. Therefore, the busy-time traffic forecasting model based ESNs (echo state networks) of multivariate principal component analysis was established. The simulation results show that the new prediction method has good generalization performance. Compared with single variable ESNs prediction model and LS-SVM forecasting model, the presented traffic forecasting method ensure the prediction efficiency while improving the prediction accuracy.

The Making of a Sustainable Wireless City? Mapping Public Wi-Fi Access in Shanghai

In the context of the global information economy, ready access to the Internet is critical to a city’s competitiveness, which has prompted a number of cities to launch plans to establish wireless networks. Most literature on the development of wireless cities focuses on cities in Western countries, and few have discussed how Chinese cities have adopted wireless technologies in their urban infrastructure development efforts. This paper examines recent development and spatial distribution of public Wi-Fi access in Shanghai, a leading business hub in China. We mapped Wi-Fi hotspots through the government sponsored “i-Shanghai” project and China Mobile Communications Corporation (CMCC). We find that while telecommunication providers have been proactively deploying WLAN (wireless local area network，a proxy of public Wi-Fi or wireless access) hotspots in Shanghai, neither government sponsored WLAN hotspots nor facilities established by CMCC could cover the old traditional neighborhoods in the central city and sub-districts in remote rural areas. We also address the development of a more sustainable wireless city in Shanghai with a particular focus on digital divide and social equity issues.

Quantum prediction GJR model and its applications

In this paper, a new statistical method to deal with the quantum finance is proposed. Through analyzing the stock data of China Mobile Communication Corporation, we discover its quantum financial effect, and then we innovate the method of testing the existence of the quantum financial effect. Furthermore, the classical normal process of the Glosten–Jagannathan–Runkle (GJR) model has been changed into the quantum wave‐function distribution, which is based on the ‘one‐dimensional infinitely deep square potential well’. The research shows that the quantum GJR model can reveal the interior uncertainty of the financial market and has a better prediction availability.

Multiple optimized online support vector regression for adaptive time series prediction

Data-driven prognostics based on sensor or historical test data have become appropriate prediction means in prognostics and health management (PHM) application. However, most traditional data-driven prognostics methods are off-line which would be seriously limited in many PHM systems needed on-line predicting or real-time processing. Furthermore, even in some on-line prediction algorithms such as Online Support Vector Regression (Online SVR) and Incremental learning algorithm, there are conflicts and trade-offs between prediction efficiency and accuracy. Therefore, in different PHM applications, prognostics algorithms should be on-line, flexible and adaptive to balance the prediction efficiency and accuracy. An on-line adaptive data-driven prognostics strategy is proposed with five various optimized on-line prediction algorithms based on Online SVR. These five algorithms are improved with kernel combination and sample reduction to realize higher precision and efficiency. These algorithms can achieve more accurate results by data pre-processing and model optimization, moreover, faster operating speed and lower computational complexity can be obtained by optimization of training process with on-line data reduction. With these different improved Online SVR methods, varies of prediction with different precision and efficiency demands could be fulfilled by an adaptive strategy. To evaluate the proposed prognostics strategy, we have executed simulation experiments with Tennessee Eastman (TE) process. In addition, the prediction strategies are also applied and evaluated by traffic mobile communication data from China Mobile Communications Corporation Heilongjiang Co., Ltd. Experiments and test results prove its effectiveness and confirm that the algorithms can be effectively applied to the on-line status prediction with increased performance in both precision and efficiency.

Service innovation and competitive advantage with the perspective of system dynamics - using China Mobile as an example

To explore the mutual strategic and conditional relationship between service innovation and competitive advantage, this paper used case studies and a literature research to explore how competitive advantage can be reached through service innovation. Making use of system dynamics, (suitable for the analysis of dynamic, complex non-linear relationships), the analysis of systematic behaviour and the causal feedback loop model, this paper summarised the key driving factors that shape competitive edge into three core competencies: the ability to respond to the environment, strategy adaptation, and learning and innovation capacities. In this study, the tactical actions of the China Mobile Communications Corporation (CMCC), whose service innovation surpasses that of its competitors, is used as an example. The path of its development services, strategic choices and innovation performance are used as a case study to verify this study’s argument and to offer a reference to the speculation on academic research and v...

CRM practice in an emerging market: The case of China Mobile

This study uses the case of China Mobile Communications Corporation to explore CRM practice in an emerging economy. While still in its infancy and with many deficiencies, China Mobile adapted its CRM practice to China market successfully. It does focus on key customers, but never gives up unprofitable customers. In fact, China Mobile has done a lot to cultivate the low-end market and is being rewarded now. China Mobile also has targeted influential work units to develop a big group clients market and run its CRM marketing like B2B industries successfully. Due to poor data quality and fast market change, it relies on both technology and intuition to organize around CRM and manage knowledge. It is suggested that organizations in emerging economies should adopt a middle way and a developmental vision in CRM practice to keep a balance between the global and local, the present and future. Key words: CRM, emerging economy, group client, individual user, technology, intuition.