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Research On Several Optimization And Decision Problems In CDMA Network Management

Posted on:2012-04-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y G ShiFull Text:PDF
GTID:1228330467981166Subject:Systems Engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of communication technologies, China Telecom’s CDMA network operating system has upgraded smoothly from the second generation CDMA1X system to the third generation CDMA20001X RevA system, which can carry the voice service and multi-rate data services with up to3.1Mbit/s. The multi-service has been becoming one of the most significant features in the current CDMA network. Different services have different data rates and QoS requirements, which induces that the users will put forward higher requirements of performance and perception when they enjoy the3G networks’high-speed wireless Internet. Therefore, it become increasingly prominent how to effectively solve optimization and decision problems in CDMA network management, which not only requires the application of advanced information technology and communication technology, but also relies on systems engineering theories and the modern management decision methods in order to provide the high-quality network service to the users, and build the high-quality network platform of the multi-service applications in the mobile Internet.In this paper, we make an in-depth study on several optimization and decision problems in management of CDMA network using the systems engineering theories and the modern optimization methods based on the practical CDMA network system in a city. The main contents of this paper are summarized as follows:(1) The CDMA network system theories were introduced, which includes of the CDMA standards evolution family and their characteristics and network structure, are introduced firstly; the research papers on the CDMA network management are then reviewed in both two perspectives of issues and methods; finally some optimization decision methods, which are used in our research, are introduced briefly.(2) The base station planning (BSP) problem is a focus problem in the strategic level of the CDMA network management. In order to address the multi-service CDMA network BSP problem, a multi-objective mathematical model, which is to minimize the cost and power consumption respectively, is built firstly and a solution algorithm based on NSGA-II is then designed. Finally one actual case is used to examine the validity of the proposed model and algorithm.(3) To improve the efficiency of the CDMA network management and enhance the user perception of network quality, a management decision support system of CDMA network is designed based on an artificial intelligence method, which is called as case-based reasoning. The overall framework and work flow of the designed system are given firstly and some key technologies are then discussed in detail. Finally the effectiveness of system operation is demonstrated according to the CDMA networks daily management data.(4) The parameter optimization problem is a key problem of optimization and decision in the operative level of CDMA network. In order to address the parameter optimization problem in the multi-service CDMA network, a mathematical model, which takes the coverage rate into account, is built firstly and a solution algorithm, which is called as constrained optimization genetic algorithm, is then designed for the proposed model.(5) In order to further enhance the efficiency of CDMA network management, the Six Sigma method is used to analyze the internal and external customer needs from the quality of telecommunications services in accordance with the DMAIC model, the use of Kano, VOC and CTQ’S associated with transformation, Parteo and fish bone diagram, FMEA identified Key factors. A detailed improvement measure is developed to implement effective control and a DT/CQT measurement system is evaluated using the DT/CQT test through the actual data of the CDMA network management.
Keywords/Search Tags:CDMA network manaegement, Base station planning, CBR, DMAIC, parameter optimization
PDF Full Text Request
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