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We present a framework for including model uncertainty into Monte Carlo simulations used for estimating interference risks. Through case studies based on a proof of concept implementation using SEAMCAT, we also illustrate how large impact model uncertainties can have on estimated interference probabilities. We argue that especially propagation model related uncertainties can be severe, and should...
In the recent years there has been an effort for the wireless systems to become more efficient in terms of power consumption and coverage planning. One aspect of this effort was the proposal of using spatial estimation approaches, that exploit the spatial correlation of the shadowing and received power, to improve propagation prediction. In this demonstration, we present a software tool that implements...
We report, based on extensive propagation measurements, cases where typical assumptions regarding shadow fading do not hold. These assumptions include universally assumed Gaussian marginals and exponentially decaying uniform spatial correlation structure. Our results are based on measurement campaigns conducted on three different environments, namely in urban, suburban and forest areas. We discuss...
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