AI based 5G optimization System with GUI

The novelty of this project lies in its use of AI to achieve real-time, proactive, and personalized optimization of 5G networks. Existing AI-based approaches often focus on specific aspects of network optimization, such as spectrum allocation or traffic management. Our project takes a holistic approach, using AI to optimize all aspects of the network, including resource allocation and the user experience.

This project also emphasizes the use of AI for predictive optimization. This means that our AI models can anticipate network problems before they occur, allowing us to take preemptive action to prevent disruptions and maintain network performance.

The main features of this project are:

1. Proactive identification of network congestion and resource bottlenecks before they occur.

2-optimized experiences for different types of applications and users.

3-Optimization of resource allocation across the network.

4-self-optimizing features to continuously improve network performance.

5: Reduced need for manual intervention and streamlined network management.

6: Rapid response to dynamic network conditions and changing user demands.

7: Immediate adjustments to maintain network performance and user experience.

8-Integrated solution for overall network optimization.

9: Automated optimization processes and adaptive network management.

Forecasting Model

Forecasting models are essential tools in the realm of telecommunications, particularly in the management and optimization of 5G networks. These models utilize historical data to predict future trends, behaviors, and values of key performance indicators (KPIs). By leveraging statistical and machine learning techniques, forecasting models provide valuable insights that enable proactive decision-making and resource planning.

Anomaly Detection Model

The anomaly detection model plays a crucial role in monitoring and identifying abnormal behaviors or events within the telecommunications network data. Anomalies, also referred to as outliers or deviations from normal patterns, can indicate potential issues or irregularities that require attention from network operators. Anomaly detection involves the process of identifying unexpected or unusual patterns that do not conform to the expected behavior of the system.

Power Optimization Model

The primary goal of the power optimization model is to ensure efficient use of network resources while maintaining the required power levels for downlink transmission. By optimizing parameters such as the Modulation and Coding Scheme (MCS) index, the number of allocated Physical Resource Blocks (PRBs), and other related factors