Impact of System-Specific Factors on Scheduling and Resource Allocation in mmWave IAB Networks

The use of millimeter-wave (mmWave) frequencies by 5G/5G+ technology results in increased signal attenuation naturally requiring dense network deployments. However, traditional fiber-based backhauling proves costly for network operators. To address this issue, 3GPP proposed the Integrated Access and Backhaul (IAB) concept to enable wireless backhaul and reduce deployment costs. However, system dynamics such as user mobility and traffic variations challenge system optimization and may shift the performance from its optimized state. On top of this, in-band mmWave IAB networks are subject to the half-duplex constraint, which prevents simultaneous transmission and reception. These limitations present challenges in optimizing the IAB network. Therefore, the goal of this study is to provide a computationally-efficient methodology for resource allocation and user scheduling in mm Wave IAB networks considering the aforementioned system limitations and constraints. Moreover, we evaluate the influence of system-specific factors and dynamics on the optimization of IAB networks and the time that it takes for the system to deviate from its optimized state. Our results show that by employing an optimally-parametrized scheduler, the throughput gain is 55% as compared to the baseline, where the radio resources are split equally among the users. The cell size is the primary parameter affecting the optimization gain, i.e., smaller cell sizes result in diminishing benefits when utilizing optimized algorithms.