The postprocessing resolution required for accurate RF coverage validationand prediction

With the trend of cellular providers shifting to higher frequencies, there is an increasing migration to smaller cells that is further driven by the g rowing demand for wireless Internet service. This obviously calls for highe r resolution RF validation and prediction, Yet, to our knowledge, there has been no study as to what resolution is required for accurate RF modeling a nd prediction, Many of today's computer prediction tools can provide estima tes of RF signal strength at arbitrary spatial resolution. However, the cho ice of this resolution is often left up to the discretion of the user. Even worse, sometimes the prediction resolution is hard-coded to be the same as that of the terrain database. Choosing a resolution bin size that is too s mall is both computationally inefficient and unnecessarily wasteful of valu able memory resources. Choosing a resolution bin size that is too coarse in troduces ubiquitous uncertainty about the quality of RF coverage. This pape r investigates the spatial quantization noise requirements of RF prediction and RF coverage validation. It is found that the minimum resolution bin si ze required to mitigate spatial quantization noise effects is about one-for tieth of the cell radius.