Performance analysis and optimization of enterprise wireless networks based on 802.11ax technology

With the rapid development of information and communication technology, the demand for wireless network technology has increased significantly. Wi-Fi is easy to implement in workplaces and educational environments, allowing users to access the internet anytime and anywhere. Wi-Fi technology has become an essential part of modern communication infrastructure for both individual and enterprise users. With the increasing number of devices and growing data demands, optimizing Wi-Fi networks for performance and reliability has become necessary, especially in enterprise environments. This study focuses on analyzing and improving the performance of an enterprise wireless network using advanced tools to identify problems and implement effective solutions. The research aims to comprehensively analyze Wi-Fi networks in terms of performance parameters, suggest optimization strategies, and contribute to academic and technical literature by providing real-world solutions. The main purpose of this research is to evaluate and improve the performance of an enterprise Wi-Fi network using Ekahau AI Pro software and Ekahau Sidekick devices. The study examines critical performance metrics such as signal strength, signal-to-noise ratio (SNR), data transfer rates, throughput and channel overlap. These metrics form the basis for identifying shortcomings and developing strategies to increase network efficiency and reliability. The research also highlights the importance of filling existing knowledge gaps and informing similar initiatives in other environments by implementing practical, real-world solutions. The measurements were first carried out in an office environment using the automatic planner feature of Ekahau AI Pro software, followed by field measurements using Ekahau AI Pro software installed on an iPad and the Ekahau Sidekick device. The Ekahau AI Automatic Planner feature was used to provide quick and effective simulation of wireless network design. This study was conducted in a corporate facility consisting of three main buildings named A, B, and C. Performance tests were carried out using Ekahau AI Pro software and the Ekahau Sidekick device. Various performance metrics such as signal strength, signal-to-noise ratio (SNR), data rate, throughput and channel overlap were examined to evaluate network effectiveness and identify areas needing improvement. The wireless network analysis assessment was conducted according to Ekahau best practices. The values determined within this assessment reflect the coverage requirements necessary for optimal network performance. Signal strength was set at a minimum of -67 dBm in both 2.4 GHz and 5 GHz frequency bands. Secondary signal strength should be at least -67 dBm in the 2.4 GHz and 5 GHz bands. The signal-to-noise ratio (SNR) should be 20 dB for 2.4 GHz and 25 dB or higher for 5 GHz. Data rate should be at least 24 Mbps in both frequency bands. Additionally, channel overlap at minimum signal strength should be -85 dBm from 2 access points in the 2.4 GHz band and -85 dBm from 1 access point in the 5 GHz band. These parameters were determined according to Ekahau best practice standards to ensure efficient and reliable operation of the wireless network. Initial findings revealed significant shortcomings in network design and performance. Specifically, signal strength measurements in some areas reached values as low as -85 dBm, leading to connection interruptions and reduced coverage area. In contrast, areas with signal strength above -67 dBm provided stable and reliable connections. However, performance was negatively affected due to errors in access point (AP) placement. In secondary signal strength assessments, areas where signal strength was above -67 dBm in the 2.4 GHz and 5 GHz bands showed that mobile clients could seamlessly transition between APs, ensuring network redundancy. However, roaming support was inadequate in areas below -67 dBm, negatively affecting network stability. Secondary signal strength in the 5 GHz band can cause connection interruptions during roaming operations, especially in these regions. This made it difficult for mobile devices to maintain continuous and reliable network connections. For successful data transmission, signal strength needs to be higher than environmental noise. In signal-to-noise ratio (SNR) assessments, areas where measured SNR levels were 30 dB and above in both 2.4 GHz and 5 GHz frequency bands provided ideal connections with fast and stable data transmission. However, significant drops in network performance were observed in areas where SNR levels fell below 10 dB. In particular, values between 0-10 dB led to connection interruptions and serious slowdowns in data transmission. This finding shows how critical it is to maintain balance between environmental noise and signal strength, and indicates the need for improvements in areas with low SNR levels. Looking at data rate results, the data rates achieved in 2.4 GHz and 5 GHz frequency bands provide important information about network performance. In the 2.4 GHz band, data rates showed a performance range varying between 1 Mbps and 300 Mbps. In the 5 GHz band, this range varied between 1 Mbps and 585 Mbps. Network performance was observed to work more efficiently in areas where high data rates were achieved. However, areas measured with low data rates experienced a noticeable decrease in network performance. This indicates the need for layout adjustments and improvements to increase network capacity and provide more stable data transmission. Network capacity (Throughput) analyses reflect an important parameter that determines the data transmission speed and efficiency across communication channels in both 2.4 GHz and 5 GHz frequency bands. This parameter is a critical measure that directly affects user experience. While network capacity values in the 2.4 GHz frequency band varied between 1 Mbps and 240 Mbps, these values ranged from 1 Mbps to 420 Mbps in the 5 GHz band. Areas with high network capacity showed more stable and efficient network operation. However, regions with low network capacity experienced slower data transmission and significant drops in connection quality. These findings indicate the need to increase network capacity and improve performance. Channel overlap is a condition that leads to network performance degradation when multiple access points using the same frequency channel interfere with each other. During analysis, it was found that the number of access points broadcasting on the same channel reached up to 6 in some areas. This situation causes channel overlap, especially in high-interference areas, and can negatively affect network performance. Channel overlap reduces data transmission speed, decreases connection stability, and causes network delays. It was determined that adjustments in channel placement and management were necessary to prevent such problems. Various improvements were implemented based on the performance issues detected in the wireless network. As part of signal strength improvements, new access points were added and existing access point locations were reorganized to solve low signal strength and efficiency problems. Additionally, access point output powers were optimized to improve signal distribution. To address roaming issues, access point positions and directions were reconfigured, and secondary signal strength levels were increased. These signal strength improvements not only solved low signal strength problems but also improved low SNR (Signal-to-Noise Ratio) values, increasing network performance. As a result, these improvements reduced connection interruptions and provided more stable, uninterrupted roaming performance. To reduce channel overlaps and improve network performance, access points' frequency and channel configurations were optimized. In the 2.4 GHz band, 2.4 GHz transmission was disabled in areas experiencing overlap due to limited channel structure. In the 5 GHz band, channel width was limited to 20 MHz, and static channel assignments were made to each access point independently to prevent overlaps. These improvements largely eliminated channel overlaps, contributing to more stable and high-performance network connections. Each floor in the facility was upgraded to serve an average capacity of 200 end users. The findings of this study show that correct AP placement and channel configuration directly affect network performance. Improvements aimed at enhancing weak signal areas and reducing interference increased network stability and ensured continuous connectivity. From a security perspective, a stable network design contributes to creating secure communication environments by reducing risks such as unauthorized access and data loss. In future studies, the advantages of Wi-Fi 7 technology's 320 MHz wide channel structure and 6 GHz band in high-density environments could be investigated. Additionally, AI-supported network management systems in areas such as channel optimization and dynamic resource allocation could be examined.