Performance Evaluation of Self-optimising Mobile Radio Networks in Realistic Scenarios

Currently, mobile radio network operators face decreasing per user revenues while at the same time capacity demands on mobile radio networks rise. Furthermore, network complexity increases as technology evolves and the simultaneous operation of several networks of different technologies is required. As a consequence, network operators seek for ways to operate their networks more efficiently. In this context, so called self-organising functionality is envisioned for integration into cellular mobile radio networks. Self-organising functionality is supposed to automate a variety of operational task, leading to better and more efficient network operation. Since performance and reliability of self-organising approaches are strongly related to the operation conditions they are exposed to, simulation under realistic circumstances is of great importance. This paper presents an approach for the evaluation of resource allocation algorithms in realistic environments based on real measurements. Furthermore, it presents an approach allowing the application of convex optimisation techniques for radio resource allocation and evaluates the proposed approach in a realistic environment using the presented evaluation approach. The performance and the suitability of the proposed resource allocation approach for self-organising optimization of future mobile radio networks are shown.