Construction of the RSRP map using sparse MDT measurements by regression clustering

Radio environment maps are geographical maps with overlaid performance information of radio communication systems, that can be considered as one of the key enablers for self-organizing networks. After the introduction of Minimization of Drive Tests (MDT) to the standards, operators are interested to generate radio environment maps based on sparse sets of MDT measurements gathered from user equipment. In this paper, we consider the construction of the Reference Signal Received Power (RSRP) map, which is an example of a radio environment map using such a sparse MDT measurement set from user equipment. In particular, we propose a two-step algorithm for RSRP map generation which is shown to bring substantial performance improvement in terms of the mean absolute error of the predicted RSRP map as compared to the existing baseline methods, i.e., environmental-based regression and inverse distance weighting interpolation.