Reply To: Claussen model


Hi Darren,

Imagine generating a shadow fading map for a square of 10 rows and 10 columns (making 100 elements) using lognormal distribution with N(0, 8) i.e. zero mean and 8 dB standard deviation. You can visualize this in MATLAB with shadowFadingMapUncorrelated = lognrnd (0, 8, 10, 10). Each of the resulting 100 elements (10 by 10 matrix) is uncorrelated (each element is independent of the other).

However, due to mobility, shadow fading is modeled as either time or space-dependent. The Vienna SLS adopts the space-correlation following the Claussen Implementation. This means that the eventual value of each element in the 10×10 matrix becomes dependent on (or correlated with) other values in the map or ROI. Claussen’s implementation simplifies the required computational complexity/memory requirement such that instead of each element being dependent on the remaining 99 elements, it is only dependent on the values of its n-neighbors where n = {4, 8 or 12 in Vienna } without significant loss in performance.

The mathematics and the implementation of the correlation can be found in the Claussen paper (See ) and the Vienna SLS tool, respectively.

Bets regards,


  • This reply was modified 3 years, 7 months ago by Sherif.