Self organization and self optimization of wireless networks with partial system knowledge

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In the future, mobile communication networks will need to provide new services and therefore will have to fulfill new requirements regarding data rates, stability and connectiveness, as well as other qualitative criteria. Because of the high mobility of an increasing number of users, networks must be virtually everywhere and consistently available. On the other hand, costs for the networks and the services provided cannot be too high. If the networks themselves can be run and maintained for low cost, the network supplier and network provider have a competitive edge. For example, savings can be achieved by shutting down a base station that is no longer needed, if the same quality of service can be provided by a neighboring base station alone.Essentially, future mobile communication networks must be equipped with the capability to adapt to time-variable quality of service requirements. They also must be able to react quickly to harmful alterations and anomalies. Therefore, within the framework of the requested research proposal, methods of reactive auto-optimization under system uncertainty will be developed and researched. In order to support the complex calculations of the underlying systems, and on the other hand, to also enable an optimization with a low complexity, it is necessary to have methods of approximation that portray the essential causations and dependencies. The treatment of this topic is of major importance for the long-range relevance of future mobile communication networks self-organization as well as to the success of the mobile communication network standards LTE (Long Term Evolution) and LTE-A. The work that is planned within the framework of this research, as well as the fundamental principles from the varying areas of engineering and mathematics, is explained in the following proposal.