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Optimizing Femtocell Networks for Enhanced Indoor Coverage.

EasyChair Preprint 14650

7 pagesDate: September 2, 2024

Abstract

This project focuses on improving the performance of femtocell networks, which are small cellular base stations designed to enhance indoor wireless coverage. As the demand for wireless communication continues to grow, femtocells often face challenges like network congestion and signal interference, leading to a decline in service quality. To address these issues, the project utilizes a detailed dataset that includes critical parameters such as signal strength, signal-to-noise ratio (SNR), call duration, user identification, environmental conditions, and the distance between the user device and the femtocell tower. These data points form the foundation for a comprehensive approach to mitigating network congestion and enhancing the overall Quality of Service (QoS). The project’s methodology is structured into several key phases, starting with data loading and cleaning to ensure accuracy and reliability. Exploratory data analysis (EDA) is then conducted to uncover patterns and trends that influence network performance. Congestion detection is performed by setting thresholds for SNR, signal strength, and user density, supplemented by cluster analysis using the KMeans algorithm to identify underlying factors contributing to congestion. A RandomForestClassifier is employed for predictive modeling, forecasting congestion events with high accuracy. Finally, optimization strategies such as dynamic power control, load balancing, and resource allocation are implemented to improve network performance. This systematic, data-driven approach demonstrates the effectiveness of machine learning and predictive analytics in enhancing femtocell networks, providing a robust framework for future innovations in wireless communication.

Keyphrases: Femtocell networks, Network Congestion, Optimization., Quality of Service (QoS), data analysis, machine learning, predictive modeling, signal strength

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:14650,
  author    = {G Chandrashekar and P Jayarekha},
  title     = {Optimizing Femtocell Networks for Enhanced Indoor Coverage.},
  howpublished = {EasyChair Preprint 14650},
  year      = {EasyChair, 2024}}
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