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This paper is concerned with UMTS radio network design. Our task is to reconfigure antennas and the related cells as to improve network quality. In contrast to second generation GSM networks, \emph{interference} plays a paramount role when designing third generation radio networks. A known compact formulation for assessing the interference characteristics of a radio network as coupling relations between cells based on user snapshots is generalized to statistical average load. This enables us to overcome the notorious difficulties of snapshot-based network optimization approaches. We recall a mixed-integer programming model for the network design problem that is based on user snapshots and contrast it with a new network design model based on the average coupling formulation. Exemplarily focusing on the important problem of optimizing antenna tilts, we give computational results for a fast local search algorithm and the application of a MIP solver to both models. These results demonstrate that our new average-based approaches outperform state-of-the-art snapshot models for UMTS radio network optimization.
The performance evaluation of W-CDMA networks is intricate as cells are strongly coupled through interference. Pole equations have been developed as a simple tool to analyze cell capacity. Numerous scientific contributions have been made on their basis. In the established forms, the pole equations rely on strong assumptions such as homogeneous traffic, uniform users, and constant downlink orthogonality factor. These assumptions are not met in realistic scenarios. Hence, the pole equations are typically used during initial network dimensioning only. Actual network (fine-) planning requires a more faithful analysis of each individual cell's capacity. Complex analytical analysis or Monte-Carlo simulations are used for this purposes. In this paper, we generalize the pole equations to include inhomogeneous data. We show how the equations can be parametrized in a cell-specific way provided the transmit powers are known. This allows to carry over prior results to realistic settings. This is illustrated with an example: Based on the pole equation, we investigate the accuracy of average snapshot'' approximations for downlink transmit powers used in state-of-the-art network optimization schemes. We confirm that the analytical insights apply to practice-relevant settings on the basis of results from detailed Monte-Carlo simulation on realistic datasets.
Planning UMTS Radio Networks
(2008)