A Self Optimising Algorithm for WCDMA Neighbour Lists Using Fuzzy Logic

In this paper a self optimising algorithm for neighbourcell lists in a WCDMA Network is proposed. The effect of a missing WCDMA cell that should be defined as a neighbour degrades network performance. It is likely to cause interference, resulting in bad quality or a dropped connection. The radio environment and network is a dynamic system and the original neighbour plan needs to be auto tuned in order to be effective. New clutter with the addition of buildings and new sites for example with their radio pollution warrant the method of auto tuning neighbour cell lists. Network outages, planned or unplanned, contribute to poor user experience. Prediction based neighbour cell lists are not optimal. An algorithm that utilises a measurement based approach to update neighbour lists automatically with selection priority is proposed. Parsed data is analysed with fuzzy logic, optimised neighbour lists with selection priority are generated and downloaded into the network. The proposed algorithm for automated optimization of neighbor cell lists was trialled and validated in a live WCDMA network. The Experimental results showed the described methodology to bean optimal solution for self-optimising WCDMA radio access networks.