| dc.description.abstract | This thesis investigates the deployment of 28GHz millimeter wave (mmWave) technology, suitable for indoor coverage in 5G mobile communication networks. The research employs two different intelligent algorithms—Fuzzy C-Means (FCM) clustering and Particle Swarm Optimization (PSO)—to rapidly identify the optimal locations for base stations in large indoor spaces.
Before deploying a 5G mobile communication base station, site surveys are necessary to assess the environment, including coverage areas, obstacles, and spatial dimensions. Hence, the choice of base station location is crucial. Millimeter waves, characterized by short wavelengths, high path loss, and low penetration, are more suited for indoor environments compared to outdoor spaces. These properties also enable 5G networks to achieve higher bandwidth, lower latency, and enhanced connectivity.
This research utilizes the powerful simulation software Matlab to design various indoor scenarios and generate random user coordinates. Fuzzy C-Means is used to identify the centroids of user clusters, which serve as potential deployment points for mmWave base stations. FCM is frequently applied in communication network scenarios to deploy nodes by clustering user populations around optimal centroids. PSO, another widely used intelligent algorithm, is common in sensor deployment applications. It guides particles in a population towards better regions based on their adaptability to the environment, efficiently searching through large solution spaces to find optimal base station locations.
The goal of this study is to evaluate the impact of these algorithms on key performance indicators of wireless communication networks, including user throughput, Signal to Interference plus Noise Ratio (SINR), and overall coverage area. By simulating mmWave base station deployments in Matlab, the performance of FCM and PSO under identical scenario designs is compared. Additionally, the study contrasts these algorithmic results with the traditional deployment strategies used by engineers to identify their advantages and disadvantages, helping to optimize base station layouts quickly and enhance the overall performance and reliability of mobile networks.
Due to the high frequency of mmWave communication, several factors, including physical obstacles, diffraction, poor penetration capabilities, and reduced coverage area compared to lower frequency bands, must be considered along with the mobility of end users. Currently, telecommunications operators focus on deploying mmWave networks in large indoor spaces, aiming to maximize coverage and user density. Indoor environmental factors, such as partition materials, decor, and electrical equipment, can also interfere with signal quality. By comparing FCM and PSO, this study assists engineers in quickly identifying better mmWave base station locations based on existing building dimensions and user density. The focus is on optimizing signal quality and strength at deployment points to ensure maximum coverage, network consistency, and stability, thereby improving the overall performance and reliability of mobile networks for users. | en_US |