Statistical Characterization and Modeling of Indoor RF-EMF Down-Link Exposure

Area of Science:

• Environmental Health
• Electromagnetic Engineering
• Statistical Modeling

Background:

• Public concern over radio-frequency electromagnetic field (RF-EMF) exposure from wireless systems is rising.
• Indoor environments account for over 70% of daily human exposure, making indoor RF-EMF assessment critical.
• Deterministic RF-EMF assessment is complex due to environmental variables and unpredictable factors.

Purpose of the Study:

• To develop a statistical model for indoor RF-EMF down-link (DL) exposure.
• To characterize RF-EMF DL exposure variability within indoor environments.
• To simplify the assessment of indoor RF-EMF exposure from cellular technologies.

Main Methods:

• Statistical analysis of RF-EMF DL exposure measurements in three buildings.
• Application of the one-sample Kolmogorov-Smirnov test to measurement data.
• Validation using a leave-one-out cross-validation technique.

Main Results:

• Indoor RF-EMF DL exposure on each floor of a building wing is a random process.
• The distribution of indoor RF-EMF DL exposure follows a Gaussian model.
• Exposure can be effectively characterized by mean and standard deviation parameters.

Conclusions:

• Indoor RF-EMF DL exposure on each floor over the length of a wing can be reliably modeled using a Gaussian distribution.
• The Gaussian model simplifies the characterization and assessment of indoor RF-EMF exposure.
• This statistical approach addresses the complexities of deterministic indoor RF-EMF assessment.