Techno – Economic Analysis of Optical Fronthaul Network Implementation in 5G-Systems
In the rapidly expanding world of the Internet of Things (IoT), the number of devices connected to IP networks is expected to surpass the global population by the end of 2024. This growth is driven by advancements in mobile communication, particularly 5G technology. The increasing device connectivity has led to more RRU (Remote Radio Head) antenna sites and higher traffic volumes requiring efficient transmission to centralized BBU (BaseBand Unit) units. However, the fronthaul network connecting RRU and BBU units faces challenges due to traffic volume, connection density, and quality-of-service demands. Passive Optical Networks (PON) have emerged as a promising solution for these issues, offering cost-effective components, high link capacity, and low latency, making them ideal for integration with 5G systems.
This paper explores the significance of 5G for IoT development and examines optical fronthaul networks in this context. It analyzes radio access network (RAN) architectures, including centralized RAN (CRAN), and reviews fronthaul systems and TWDM PON networks within 5G architectures. The thesis also focuses on minimizing the Total Cost of Ownership (TCO) in 5G implementations by optimizing capital (CapEx) and operational expenditures (OpEx). A mathematical model using the Integer Linear Program (ILP) approach is proposed, along with two heuristic algorithms: K-means clustering and Genetic Algorithm (GA). These algorithms are evaluated through a case study, incorporating real-world implementation parameters. Results are presented with diagrams, tables, and figures, offering insights into the methodology's practical implications.