Path Loss Visualizer

Background: Received signal power decays with distance from a transmitter. The free-space path loss model predicts loss (PL, in dB) growing as 20log₁₀(d), assuming an unobstructed line of sight. Real-world environments deviate from this because of reflection, diffraction, and scattering, which is captured by the more general log-distance path loss model PL(d) = PL(d₀) + 10n·log₁₀(d/d₀), where d₀ is a reference distance, the path loss exponent n depends on the environment (larger in dense urban areas, smaller outdoors), plus a random lognormal shadowing term (a zero-mean Gaussian random variable in dB, with standard deviation σ) that accounts for the scatter of measurements around that mean trend.

Description of This Web Application: Pick a propagation environment (urban, suburban, rural, or indoor), a distance range, a center frequency, and a shadowing standard deviation, and the app generates 50 synthetic measurements consistent with that model. It plots both the ideal free-space path loss curve and the fitted lognormal shadowing curve (with ±1σ bounds) against your measurements, and uses least squares to estimate the path loss exponent directly from the noisy data. You will see how the path loss exponent varies by environment, why shadowing scatters measurements around the mean trend rather than following it exactly, and how a simple linear regression can recover propagation parameters from field measurements.