Performance Analysis and Optimization of Enterprise Wireless Networks Based on 802.11ax Technology
This study focuses on performance analysis and optimization of enterprise wireless networks. Fundamental performance parameters of Wi-Fi networks such as signal strength, signal-to-noise ratio (SNR), data rate, and channel interference were evaluated in detail in the study. The analysis process was...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sakarya University
2025-06-01
|
| Series: | Sakarya University Journal of Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/en/download/article-file/4398347 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This study focuses on performance analysis and optimization of enterprise wireless networks. Fundamental performance parameters of Wi-Fi networks such as signal strength, signal-to-noise ratio (SNR), data rate, and channel interference were evaluated in detail in the study. The analysis process was carried out using Ekahau AI Pro software and Ekahau Sidekick device in a corporate facility, consisting of three main buildings. The obtained data revealed that signal strength dropped to -85 dBm levels in certain areas, negatively affecting the network's coverage area. Particularly in the ground floor of building B-C, secondary signal levels were found to be insufficient for roaming. Across the campus, SNR levels were observed to be 30 dB and above, and these values were found to provide ideal connectivity. During the analysis, it was discovered that in some areas, the number of access points broadcasting signals on the same channel increased up to 6. It has been assessed that this situation may negatively affect network performance in areas where interference is intense. Data rates varied between 1 - 300 Mbps in the 2.4 GHz frequency band and 1 - 585 Mbps in the 5 GHz band. The study provides significant data for performance analysis and optimization of enterprise wireless networks. |
|---|---|
| ISSN: | 2636-8129 |