SON Use Cases Coordination Management In Heterogeneous Wireless Networks

In heterogeneous wireless networks, new characteristics, such as heterogeneity, complexity, dynamics and openness, etc, have been shown gradually in the heterogeneous networks. The heterogeneous wireless network must be dynamically to meet the needs of users to guarantee the quality of services and good user experience, due to the reason that the users are very sensitive for the quality of service provided by wireless network. Traditional artificial operation for network optimizing, configuration and network healing is time-consuming and inefficient, and it costs large OPEX for more complex wireless network. SON(self-organized network) concept is introduced in LTE wireless access network to realize self-organization and self-optimization in order to solve the problem. Self-organizing network can realize operation, control and optimization independently, so it has become a hot issue to design a self-organizing network management mechanism in heterogeneous network in the future. However, different SON functions have different relations with each other, which will cause possible conflicts between different SON functions when optimize for different optimization targets. And the possible conflicts can decrease the network performance. Hence, a great attention has been paid to the consistency and coordination management between different SON functions to avoid the possible conflicts and to improve the network performance.Aims of this thesis are analyzed the conflicts and proposed a novel consistency and coordination management scheme, which can avoid the possible conflicts and improve the network performance, according to the wireless network parameters and key performance indicators(KPI) in heterogeneous wireless network. First of all, this paper studied the relationship between KPI and wireless network resource management(RRM) parameters and modeled it based on the theory of logistic regression. We can adjust the parameters of RRM by running the corresponding SON functions to meet the KPI values according to the model. And in return, we can also modify the KPI values to meet the special parameter values to improve network performance. Furthermore, we studied the conflicts between SON functions which have the same timescale. Specially, the conflict between load balancing function and mobility robustness optimization function is discussed and a novel resolution strategy is given. Finally, theimplementation of cooperative network management strategy for energy saving is put forward under different time scales of multiple SON functions. The energy saving problem is decomposed into the base station model combination optimization problem and load balancing problem. it can realize energy saving by controlling the base station state such as open or closed,which is very important to improve energy efficiency in wireless networks.