We propose a Clustering-Driven Approach for Base Station Parameter Optimization and Automation (CeDA-BatOp), an automated framework for predicting optimized ...

Nov 2, 2023 · Our framework first compares three clustering algorithms: K- means, DBSCAN, and Agglomerative Clustering, selecting the most suitable one for ...

This clustering-driven approach enables us to group base stations based on their network parameters, which allows us to optimize them more efficiently. In ...

CeDA-BatOp 2.0: Enhanced Framework for Base Station Parameter Optimization and Automation with Joint Optimization, Controlled Drift Analysis and Pseudo-Labeling.

Dec 7, 2023 · We propose a Clustering-Driven Approach for Base Station Parameter Optimization and Automation (CeDA-BatOp), an automated for predicting optimized base station ...

May 3, 2024 · Framework: Clustering-Driven Approach for Base Station Parameter Optimization and Automation (CeDA-BatOp). Conference Paper. Jan 2024.

CeDA-BatOp 2.0 is a step forward in addressing the complexities of cellular network optimization. By combining MTL, drift analysis, and pseudo-labeling, it ...

In parallel to clustering, our framework leverages machine learning (ML) algorithms to predict the optimal parameters for each base station with an evaluation ...

Article "Framework: Clustering-Driven Approach for Base Station Parameter Optimization and Automation (CeDA-BatOp)" Detailed information of the J-GLOBAL is ...

Sudharshan Paindi Jayakumar, Alberto Conte: Framework: Clustering-Driven Approach for Base Station Parameter Optimization and Automation (CeDA-BatOp).