Performance Evaluation and Optimization of Integrated Access and Backhaul Systems

The advent of sixth-generation (6G) networks will indicate a new era in telecommunications, promising transformative improvements that may positively impact various aspects of our society. Envisioned as the successor to fifth-generation (5G), 6G networks aim to provide unprecedented connectivity, offering faster data rates, lower latency, and increased capacity. These advancements have the potential to revolutionize communications, enabling seamless connectivity for a wide range of applications. To achieve these goals, 5G and beyond networks are designed to effectively use a wide spectrum range, emphasizing the utilization of the millimeter-wave (mmWave) spectrum. However, this brings challenges to communication service providers. One of the major challenges is reduced cell range due to higher path loss and blockage effects.

To address it, a strategy known as network densification may be employed, which involves a deliberate increase in the number of base stations within a designated geographical area. However, establishing connectivity between all these sites through cabling proves to be intricate and imposes significant financial burdens. Recently proposed Integrated Access and Backhaul (IAB) technology emerges as a viable solution to all these challenges. IAB aims to streamline network architecture, enhance efficiency, and simplify deployments, especially in dense urban environments or areas with limited fiber connectivity.

The efficient operation and optimization of IAB networks are required to achieve improved system performance. However, the increased complexity of these systems necessitates the development of new, efficient, and low-complexity solutions that are imperative for network operators to manage these advanced systems effectively. This thesis proposes a set of mathematical frameworks and simulation tools for performance evaluation and optimization of various IAB systems. It addresses key challenges and opportunities in IAB systems and their integration with emerging technologies such as unmanned aerial vehicles (UAVs).

Through a series of methodologies and optimization frameworks, the thesis aims to enhance network performance by optimizing network topology formation, resource allocation, and link scheduling. The simulation results highlight the importance of a holistic approach when optimizing IAB networks. Additionally, the main results show the significance of multi-beam functionality and streamlined time allocation patterns for IAB networks. On top of this, the study explores strategies for utilizing mmWave-capable UAV networks for data traffic offloading in urban environments, emphasizing the mitigation of blockage constraints through advanced routing techniques. These findings contribute to the advancement of efficient and reliable communication systems, offering practical insights for future deployment and optimization efforts in dynamic wireless networks.