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Log-distance path loss model

The log-distance path loss model is a radio propagation model that predicts the path loss a signal encounters inside a building or densely populated areas over long distance. While the log-distance model is suitable for longer distances, the short-distance path loss model is often used for indoor environments or very short outdoor distances. It's simpler and assumes a more direct line-of-sight propagation.

Mathematical formulation
Model Log-distance path loss model is formally expressed as: : L=L_\text{Tx}-L_\text{Rx}=L_0+10\gamma\log_{10}\frac{d}{d_0}+X_\text{g} where • {L} is the total path loss in decibels (dB). • L_\text{Tx}=10\log_{10}\frac{P_\text{Tx}}{\mathrm{1~mW}} \mathrm{~dBm} is the transmitted power level, and P_\text{Tx} is the transmitted power. • L_\text{Rx}=10\log_{10}\frac{P_\text{Rx}}{\mathrm{1~mW}} \mathrm{~dBm} is the received power level where {P_\text{Rx}} is the received power. • L_0 is the path loss in decibels (dB) at the reference distance d_0. This is based on either close-in measurements or calculated based on a free space assumption with the Friis free-space path loss model. • {d} is the length of the path. • {d_0} is the reference distance, usually 1 km (or 1 mile) for a large cell and 1 m to 10 m for a microcell. (and thus the corresponding power gain F_\text{g}=10^{-X_\text{g}/10} may be modelled as a random variable with exponential distribution). Corresponding non-logarithmic model This corresponds to the following non-logarithmic gain model: : \frac{P_\text{Rx}}{P_\text{Tx}}=\frac{c_0 F_\text{g}}{d^{\gamma}} , where c_0={d_0^{\gamma}}10^{-L_0/10} is the average multiplicative gain at the reference distance d_0 from the transmitter. This gain depends on factors such as carrier frequency, antenna heights and antenna gain, for example due to directional antennas; and F_\text{g}=10^{-X_\text{g}/10} is a stochastic process that reflects flat fading. In case of only slow fading (shadowing), it may have log-normal distribution with parameter \sigma dB. In case of only fast fading due to multipath propagation, its amplitude may have Rayleigh distribution or Ricean distribution. This can be convenient, because power is proportional to the square of amplitude. Squaring a Rayleigh-distributed random variable produces an exponentially distributed random variable. In many cases, exponential distributions are computationally convenient and allow direct closed-form calculations in many more situations than a Rayleigh (or even a Gaussian). == Empirical coefficient values for indoor propagation ==
Empirical coefficient values for indoor propagation
Empirical measurements of coefficients \gamma and \sigma in dB have shown the following values for a number of indoor wave propagation cases. == See also ==
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