Dynamic Frequency Reuse for Enhance 5G Spectrum Management

In the relentless pursuit of optimizing 5G spectrum management, this study introduces a dynamic frequency reuse scheme leveraging a symbiotic integration of Logistic Regression models and Queuing Theory. The focal point of this scheme is the seamless transition from a conservative reuse-3 pattern to a more dynamic reuse-7 configuration when the number of users surpasses 50. Through rigorous analysis and consistent observations, our findings showcase a significant enhancement in user accommodation, spectral efficiency, and overall network performance. The scheme's architecture relies on a Logistic Regression model to predict optimal transition times, while Queuing Theory principles are invoked to manage users efficiently during and after the switch. The proposed system accommodates users ranging from 51 to 65 within the reuse-7 framework, subsequently directing users exceeding this threshold to a queuing system. This innovative approach ensures that spectral resources are utilized optimally, minimizing interference, and maintaining a high quality of service. Consistent observations across various scenarios demonstrate that the dynamic transition to reuse-7 consistently results in accommodating more users within the existing spectrum. Spectral efficiency is notably improved, and the queuing system proves to be an effective mechanism for resource allocation beyond the immediate capacity of reuse-7. This abstract encapsulates the core contributions of our research, shedding light on a dynamic frequency reuse scheme that not only adapts to changing network dynamics but also systematically enhances 5G spectrum management by accommodating more users and optimizing resource utilization. The symbiosis of Logistic Regression models and Queuing Theory principles emerges as a promising paradigm for adaptive and efficient 5G network management.