| In 5G oriented mobile communication system, the demand of traffic will grow rapidly and the network deployment will be denser and more heterogeneous. A newly proposed large-time-scale environment-aware Self-organized network structure would deal with the inefficiencies arised from long-term dynamics of the cellular network, and reduce the cost of network planning and configuration.The research of environment-aware SON need to be based on complete system level simulation and RRC protocol simulation modeling. This thesis designs and implements a system level simulation platform orienting to 5G environment-aware SON. The platform consists of supporting environment, radio resource control protocol model and SON module. The performance of long-time-scale environment-aware SON under 3GPP protocol framework is able to be evaluated and researched through this platform. The details of this thesis are as follows:The first two chapters of the thesis introduce the main content, the significance of the research and the status, as well as the design requirements of the simulation platform.The details of supporting environment is provided in chapter3, such as discrete eventdriven simulating mechanism, 3D channel model, physical layer module, adaptive modulation and coding, and MAC scheduling, etc. The physical layer module needs to implement the link-to-system mapping method and reference signal modeling. The AMC module computes the TBS and implements 256 QAM and spatial multiplexing. The packets scheduling module implements some resource scheduling algorithm such as Round Robin and Proportional Fairness. Finally, the validity of the supporting environment is confirmed by being compared with calibration result in 3GPP standard or METIS technical report.Chapter4 describes the details of the RRC protocol model in simulation platform, including ideal control message modeling, RRC measurement, handover, connection controlling, and RRC KPI evaluating. The control message and information element in the platform are implemented by C++ structure and enumeration. RRC measurement functionalities includes measurement configuration, result filtering, event-based measurement report triggering, and measurement GAP for inter-frequency. Particularly, the platform must deal with the triggering cells dynamic caused by TTT mechanism. The A1/A2-based startup and termination of inter-frequency measurement is also implemented. As for handover procedure, the platform implements handover preparation, execution and handover KPI modeling. The expansibility for handover algorithms is considered. The connection controlling focus on the RRC re-establishment caused by RLF or HOF, and the T311 timer. In this chapter, test results of event-based measurement report and KPIs for handover and inter-freq measurement are provided to validate the RRC model.Chapter5 implements environment-aware SON module at the basement of supporting environment and RRC protocol model. The SON module consists of RRC information interface, environment information collector, information processing and characterizing module, SON optimization execution module. The RRC module implemented in Chapter4 is a main source of the environment information collection. In view of the deterioration of the handover performance caused by the complex and changeable heterogeneous cellular network structure, a new SON method based on environment perception is proposed. Firstly, a large number of handover events are collected as the environmental information, and then the distribution law of the high frequency HOF region is percepted through the analysis and processing of the information. Finally, the SON performs a self-optimization to the RRC measurement parameters for the high frequency switching failure HOF region, in order to enhance the mobility robustness. The proposed scheme is tested using environment aware SON simulation platform. Simulation results show that the proposed scheme can obtain the accurate handover environment distribution characteristics, and can be aware of the long time dynamic changes of the network deployment structure. This optimization can improve the handover success rate and other mobility KPIs, confirming the validity of environmentaware SON under actual protocol framework. |
