Advanced analysis methods for 3G cellular networks
| Autor: | Pasi Lehtimäki, Jaana Laiho, Kimmo Hätönen, Olli Simula, Kimmo Raivio |
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| Rok vydání: | 2005 |
| Předmět: |
Self-organizing map
Radio access network Access network business.industry Broadband networks Code division multiple access Computer science Applied Mathematics Distributed computing Telecommunications service Troubleshooting Computer Science Applications Network management Cellular network Electrical and Electronic Engineering business Cluster analysis Computer network |
| Zdroj: | IEEE Transactions on Wireless Communications. 4:930-942 |
| ISSN: | 1536-1276 |
| DOI: | 10.1109/twc.2005.847088 |
| Popis: | 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 k-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. |
| Databáze: | OpenAIRE |
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