【文件属性】：
文件名称：Advanced Analysis Methods for 3G Cellular Networks
文件大小：1.86MB
文件格式：PDF
更新时间：2018-03-30 09:21:40
3G
The operation and maintenance of the third generation
(3G) mobile networks will be challenging. These networks
will be strongly service driven, and this approach differs significantly
from the traditional speech dominated in the second generation
(2G) approach. Compared to 2G, in 3G, the mobile cells
interact and interfere with each other more, they have hundreds
of adjustable parameters, and they monitor and record data related
to several hundreds of different variables in each cell. This
paper shows that a neural network algorithm called the self-organizing
map, together with a conventional clustering method like
the -means, can effectively be used to simplify and focus network
analysis. It is shown that these algorithms help in visualizing and
grouping similarly behaving cells. Thus, it is easier for a human
expert to discern different states of the network. This makes it possible
to perform faster and more efficient troubleshooting and optimization
of the parameters of the cells. The presented methods
are applicable for different radio access network technologies.