The Challenges of RF Optimization
You just finished another calibration effort of the cellular network, but subscribers still complain! And they continue to complain, no matter for how long you keep optimizing the network.
Many times you think that there is a problem somewhere, you go there and drive test the area, but still you can’t put your finger on the problem or on the reason for it.
So much time is wasted on: complains that are not significant problems that can’t be solved in a cost effective way. You see fluctuations in many cell sector statistics, but you have no way to prioritize it: Which of these problems can be solved easily and which will take ages and a lot of money; Which of these problems has minor effect on customers and which can drive them crazy…
The gap between customers' experience and network data:
Even if cell/sector statistics are great (less than 1% dropped calls), there are always local singularity points with clusters of 10% - 20% dropped calls, which still do not make the average cell/sector drop rate high enough. These repeating problems in each a cluster are caused by the same reason in most cases. For those subscribers who go there on a daily basis, the service quality is un-bearable. Furthermore, even if these problematic points are reported, many times there is no supporting data to understand and solve the problem.
Even if you do see some anomalies in cell/sector data, test drives will rarely detect such clusters, since: test drives are very limited in number and some of the problems will only occur occasionally or during periods of network load. In addition, they may use different handset than the subscribers and sometimes you don’t know where exactly to send them in order to spot the problem.
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