<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">Radio measurements play a crucial role in mobile wireless networks as they are input of Radio Resource Management (RRM) mechanisms, needed to assess mobile network reliability and to supervise the planned coverage area. Nevertheless, these measurements are used in their crude state without any additional intelligent treatment whereas they are a rich and unexploited source of information for the network. In this paper, we propose a new approach for the manipulation of existing radio measurements in wireless mobile networks. The goal is to optimize the use of these measurements with new approaches of exploitation in different locations of the network, basing on advanced signal processing tools. This new approach is based on nonparametric regression and smoothing methods. Interesting results are inferred from this analysis, based on real measurement traces collected in different environments and situations. Main results are the elaboration of a dynamic estimator of the attenuations components (pathloss, shadowing and fast fading), a method for the determination of the mobile user situation (incar, pedestrian and unmoving) as well as ameliorations in the handover procedure. We conclude that integrating advanced radio signal processing in RRM mechanisms is an efficient and easy-toimplement way for a better use of radio measurements.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>
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