View source: R/compute_sig_strength.R
compute_sig_strength | R Documentation |
Compute signal strength (propagation). The propagation is modelled based on the physical properties of the cells. Also, the likelihood distribution is calculated, which takes the overlap of cells into account.
compute_sig_strength(cp, raster, elevation, param, region = NULL)
cp |
cellplan, validated with |
raster |
raster object that contains the raster tile index numbers (e.g. created with |
elevation |
raster with elevation data |
param |
parameter list created with |
region |
polygon shape. If specified, only the signal strength will be calculated for raster tiles inside the polygons |
a data.frame is return with the following colums: cell (cell id), rid (raster tile id), dist (distance between cell and grid tile), dBm (signal strength), s (signal dominance), pag (likelihood probability). This data.frame is required to run the interactive tool explore_mobloc
from the mobvis
package and to compute the connection likelihood with create_strength_llh
.
## Not run:
# set parameters
ZL_param <- mobloc_param()
# load data
data("ZL_cellplan", "ZL_muni", "ZL_elevation", "ZL_landuse")
# create environment layer (needed to calculate path loss exponent (ple))
ZL_envir <- combine_raster_layers(ZL_landuse, weights = c(1, 1, 1, 0, 0))
# validate cellplan
ZL_cellplan <- validate_cellplan(ZL_cellplan, param = ZL_param, region = ZL_muni,
envir = ZL_envir, elevation = ZL_elevation)
# create raster
ZL_bbox <- sf::st_bbox(c(xmin = 4012000, ymin = 3077000, xmax = 4048000, ymax = 3117000),
crs = sf::st_crs(3035))
ZL_raster <- create_raster(ZL_bbox)
# compute the signal strength model
ZL_strength <- compute_sig_strength(cp = ZL_cellplan, raster = ZL_raster,
elevation = ZL_elevation, param = ZL_param)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.