Time % and % Location Propagation

Time % and % Location Propagation are known as variability statistics within the tool. The % of Location and % of Time columns allow you to add path loss to the propagation model due to either fast (location) and/or slow (time) fading. Time fading is normally used in fixed links like microwave, where signal variation over time is dominant. Location fading is used in mobile environments where the fading is due to the mobile moving through obstructed areas.

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Both of these fields are statistical controls and the basis for calculating these factors is discussed in Appendix A. These values are given in percent in order to let the user easily add a path loss value that will, for example, ensure that any given location will have an actual received power at or above the predicted received power at whatever percent is listed. For example, with % of Location set to 50%, out of all the range of possible fading variations, the predicted signal level is adjusted so that 50% of the possible fading is above and below your predicted signal level.

The allowed range for the variability percentage selections is determined by the selected path loss calculation method. For example, when using the FCC-EDX or FCC-FCC propagation model, you will usually want to select a location percentage of 50% and a time percentage of either 50% or 10%. These selections correspond to the F(50,50) and F(50,10) propagation curves, respectively. However, you do have the flexibility of choosing F(50,90) or other statistics with FCC methods, if desired. The ITU-R method offers a greater range of selections. The basis for calculating these variability factors is discussed in Appendix A. Other time and location settings may be specified by your particular industry as well, such as public safety which usually uses 50% time and 85-95% location for mission critical systems.

Location variability is characterized by a random variable with a distribution similar to a Rayleigh distribution. The degree of variation can be estimated by recognizing that the signal level exceeded increases by approximately 10 dB for every order of magnitude change in the percent level exceeded. For example, if a predicted median signal level (the signal level exceeded at 50% of locations) is -100 dBmW, then the signal level exceeded at 90% of the locations is approximately -110 dBmW. Similarly, the signal level exceeded at 99% of the locations is -120 dBmW. This relationship applies in the other direction as well. The signal level exceeded at 10% of the locations for this example is -90 dBmW; the signal level exceeded at 1% of the locations is -80 dBmW. With some thought, application of the time and location variability signal level statistics in the program should become straightforward.