The accuracy of the A2GLPM can be enhanced by incorporating more sophisticated modeling techniques that consider the correlation between user positions and blockage probability. One approach could involve utilizing machine learning algorithms to analyze historical data and identify patterns in user positions and corresponding blockage probabilities. By training the model on a diverse set of scenarios, it can learn to capture the intricate relationships between user positions, terrain features, and blockage probabilities more effectively. Additionally, integrating advanced signal processing techniques, such as beamforming and interference mitigation, can help refine the estimation of blockage probabilities based on user positions. By leveraging a combination of machine learning and signal processing methods, the A2GLPM can be fine-tuned to better capture the correlation between user positions and blockage probabilities, thereby improving its overall accuracy.