Modeling and Optimization of Wireless fidelity (Wi-Fi) Received Signal Strength for Variables Environmental Conditions and Building Components

With the increasing reliance on wireless communication across various domains, optimizing Wi-Fi received signal strength has become crucial for ensuring reliable and efficient connectivity. This research paper presents an in-depth analysis of Wi-Fi signal strength optimization for both the 2.4 GHz and 5 GHz frequencies. The study considers key environmental factors—temperature, relative humidity, type of construction material, and distance from the Wi-Fi router—as input parameters for the optimization process. The variation range for each parameter is carefully selected to encompass a wide spectrum of real-world scenarios. By developing mathematical models and utilizing response surface methodology (RSM) as an optimization technique, this study aims to provide insights into enhancing Wi-Fi signal strength in diverse environments.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/aece62803.2024.10911846
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
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article

Modeling and Optimization of Wireless fidelity (Wi-Fi) Received Signal Strength for Variables Environmental Conditions and Building Components

S. Pratap Singh, S. C. Srivastava, Shilpa Choudhary, J. Singh
Millimeter-Wave Propagation and Modeling
article

Modeling and Optimization of Wireless fidelity (Wi-Fi) Received Signal Strength for Variables Environmental Conditions and Building Components

S. Pratap Singh, S. C. Srivastava, Shilpa Choudhary, J. Singh
article en

Abstract

With the increasing reliance on wireless communication across various domains, optimizing Wi-Fi received signal strength has become crucial for ensuring reliable and efficient connectivity. This research paper presents an in-depth analysis of Wi-Fi signal strength optimization for both the 2.4 GHz and 5 GHz frequencies. The study considers key environmental factors—temperature, relative humidity, type of construction material, and distance from the Wi-Fi router—as input parameters for the optimization process. The variation range for each parameter is carefully selected to encompass a wide spectrum of real-world scenarios. By developing mathematical models and utilizing response surface methodology (RSM) as an optimization technique, this study aims to provide insights into enhancing Wi-Fi signal strength in diverse environments.

Climate action, Life in Land
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Millimeter-Wave Propagation and Modeling
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