## 3 Results
### Identifying the Data Pattern and Identifying the Fault Cause
The third cluster contained records that were not far from the service station and had an unacceptable level of interference and signal. This meant that the path obstacles might reduce the signal strength. The interference caused by the signals of the neighboring cells should be corrected by resetting the site parameters, such as the height and angle of the antenna in the adjacent cell. Scenario number 2, short call: The purpose of this scenario was to check the network in terms of its access success rate. Many calls were attempted in this scenario. In the available data of this research, there were 8 blocked calls out of 349 calls in the short call scenario. These results showed high interference in these areas, and the signal level was insignificant. Further investigation of the reasons for blocked calls was available in performance support system indicators and is covered in Section 4. Scenario number 3: Long-term call: This scenario, which was the most critical scenario in the field test, measured signal quality, conversation quality, carrier power to interference power ratio, and advanced timing. The purpose of this scenario was to identify the state of the system on call interruptions and handovers. As seen in the following figure, among the different clustering methods applied to this data, the k-means method achieved a higher Silhouette coefficient than other methods. Therefore, we first briefly overview the k-means clustering method. The details of the results are given later in this section. The k-means method is among the best cluster partitioning methods. This means that, according to the number of clusters, there is an attempt to optimize the data division according to the similarity or distance criterion (Figure 15). Several algorithms with a different number of clusters were tried on this data. For the k-means method, the number of 4 clusters had the best answer. The Silhouette coefficient value for this cluster was 0.6269. Table 7 illustrates the obtained histogram of the features in 4 categories. The signal quality in cluster number 1 was inadequate. Low signal quality was due to low power and signal level. Paying attention to the characteristic value signal power-interference power ratio showed significant interference in the system due to the signal level. On the other hand, since the value of the advanced timer parameter was low, the decreased signal level was not the long distance from the transmitter station. Therefore, this  
Figure 15: Silhouette coefficient value of different clustering methods–long call scenario. was out of range. Thus, site design parameters, such as antenna height and angle, should be considered to reduce the coverage area or the antenna power. In cluster number 3, all features were in good condition. This cluster showed the proper state of the network. In cluster number 4, the bad quality of the signal was not caused by the power reduction and signal level or interference. On the other hand, the value of the advanced timer also showed the system's status. Therefore, according to the expert, the reason for this was hardware problems in one of the sources of sending and receiving information in antennas called TRX. Cluster number 5 showed high interference in the system. On the other hand, the signal level in this cluster was suitable. Therefore, the interference strength could be seen in the low power of the carrier signal. In this cluster, the advanced scheduler also had an acceptable value. Therefore, the reason for the existence of this problem could be attributed to the presence of interference from external sources, such as signals from other operators, or incorrect installation of sectors and the need to swap them.