Assuming that the received power is equal to the sensitivity of the victim link receiver, then the radius Rmax can be determined for the wanted radio path by the following equation.
(Eq. 163)
where the path loss is defined by a median loss plus an additional term representing the distribution
(Eq. 164)
where:
- Fmedian: propagation loss not including slow fading, i.e. path loss without variations option;
- Fslowfading(X%): slow fading margin for X% coverage loss;
The distribution of the path loss can be expressed in a general way by the following equation:
where Q is the cumulative distribution for Rmax and the resulting mean path loss and an additional path loss due to availability or coverage . The availability y of the system is linked to the coverage loss through the simple relation y = 1 – x. Assuming that slow fading can be approximated by log-normal distribution, i.e. median mean, the relation can be introduced where b stands for a multiple of the standard deviation (sigma). A few examples for illustration: At a 95 % coverage, b results in 1.96, for 99 % in 2.58, for 99.9 % in 3.29, or b=1 68 % coverage, for b=2 for 95.5 %. The exact values can be easily determined by using the inverse Gaussian function.
Here are some examples for illustration:
- for 68 % coverage, b = 1;
- for 95 % coverage, = 1.96;
- for 95.5 % coverage, = 2;
- for 99 % coverage, = 2.58;
- for 99.9 % coverage, =3.29.
The exact values can be easily determined by using the inverse Gaussian function.
(Eq. 174)
The determination of the zero of function v, is made through a recursive method such as regula-falsi used in logarithmic scale which should yield a better precision. The solution of such a method provides the following equation:
(Eq. 175)
In this case, formulas given for need to be inverted.
Then the equation:
(Eq. 165)
The determination of the zero of function v, is made through a recursive method such as regula-falsi used in logarithmic scale which should yield a better precision. The solution of such a method provides:
(Eq. 166)
In this case, formulas given for have to be inverted.
Note 1: Inverse of the normalised Gaussian cumulative distribution is implemented through a piecewise approximation.
Note 2: Ro to be set to 1 m (0.001 km)
Note 3: If after running the simulation it appears that the resulting coverage radius is equal or very close to the minimum distance or the maximum distance used in calculation of coverage radius, it is likely that there is a mistake in the values you provided. This can be solved by reducing the minimum distance or increasing the minimum distance used in calculation, so that the algorithm may find the corresponding coverage radius.
Note 4: When setting the Rmin, Rmax values, please observe the validity range as appropriate for the selected propagation model. Otherwise SEAMCAT will produce the error message when starting a simulation.