AI-Enhanced Resource Allocation in 5G-Advanced Networks Using KNN with Osprey Optimization for Next-Generation Mobile Services

Effective resource allocation becomes essential for optimal performance of $5 \mathbf{G}$ networks. In this context, this study presents a dynamic resource allocation model for 5GAdvanced networks augmented by artificial intelligence using a K-Nearest Neighbors (KNN) model optimized using the Osprey Optimization Algorithm (OOA). Using a Kaggle dataset, the model forecasts resource distribution including bandwidth and computational capability. With an MSE of 0.008, an MAE of 0.02, and a $R^{2}$ score over 0.9, the suggested model performs better than other models like Linear Regression, Random Forest, and XGBoost. The findings surpass conventional machine learning algorithms in precisely forecasting and optimizing resource allocation.