)/BTS or RAB/RRC setup failures due to AC) and high numbers of samples on traffic class 4 would indicate possible problems due to congestion. Radio Network Optimisation On-line cellavail overview On-line list of blocked cells Cell Working States Cells with SIB-problems Cells with low availability Cells with RAB but no RRC Cells with RRC Setup Failures Cells with RRC Access Failures Cells with low setup success rate Cells with many restarts Cells with high drop call rate Figure 2.99 Example problem spotting query types Using Statistics to Determine Cells to be Optimised Selecting a Bad Performing RNC Area To start an optimisation process the scope of the work needs to be defined. Even if the target is to improve overall network performance it is practical to start optimising a subset of network that is within geographical boundaries. An RNC area is a suitable geographical area to have a drive test team operating. Also the RNC level statistic is available for statistical analysis. A bad performing RNC area can be selected based on high level performance criteria, e.g. the drop call rate for voice and video and the fluctuation of performance data over days. Different criteria might include a call setup failure rate or packet data performance. It is important to have performance data from a longer period of time. In the example shown in Figure 2.101 the bad performing RNC area is selected using RNC performance trends. If the trend shows a large amount of fluctuation over a 2 week period or constantly bad performance, the RNC is selected for further investigation. Selecting Cells to be Optimised There are several ways to prioritise which cells are performing badly. Conventional practice is to select cells based on the main KPI that is to be optimised. If the target is to improve drop call rate cells are selected based on the drop call rate. However, this approach does not take into account the effect that cell has on the overall RNC performance. A more effective approach is to prioritise cells in an absolute number of