UMTS Radio Network Planning: Mastering Cell Coupling for Capacity Optimization / Advanced Studies Mobile Research Center Bremen (PDF)

4 Expected-i nterference-coupling estimates for network performance (S. 63-64)

Radio network planning aims at improving the expected network performance, so we are not interested in network performance on a single snapshot, but on the expected performance for random snapshots. The coupling matrices thus have to be considered random variables subject to a probability distribution induced by the distribution on snapshots, and we are interested in the stochastics of the performance indicators. Simulation methods are commonly used for determining mean values of performance indicators, but they are inherently too time consuming for use in heavy-duty optimization tools, therefore, faster approaches are needed.

While Monte Carlo methods can yield an arbitrary accuracy if sufficient time is granted, high (absolute) precision is dispensable for taking intermediate planning decisions. For a successful optimization campaign, the ability to quickly discriminate between design alternatives is paramount. The right decision can be made in short time, if accuracy is sacrificed in a controlled fashion. The practical relevance of quick estimation techniques is apparent from the fact that many commercial software tools advertise fast proprietary evaluation methods besides Monte Carlo simulation (Aircom International ltd, 2007, Cosiro GmbH, 2006, Ericsson AB, 2006, Lustig et al., 2004).

In this chapter, we develop methods for estimating the expected network performance with little computational effort. The basic idea is to calculate approximations to the mean values of capacity-related performance indicators based on the mean coupling matrix. The scheme depends on suitable choices of the performance model and of the random model. With the interference coupling complementarity systems, we have a detailed model that reflects the relations between cells. We restrict the random model on snapshots to exclude shadow fading, calculating with the medians of

Dr. Hans-Florian Geerdes is a scientist at Zuse Institute Berlin and at the DFG research center MATHEON: Mathematics for Key Technologies. His research focuses on applications of combinatorial optimization in wireless telecommunications.