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Model complexity vs. better parameter value estimation: comparing four topography-independent radio models

In this case study we show how four topography-independent radio models (models not regarding individual obstacles in the operations area) can be "tuned" such that the outcomes of an event-driven network simulator come as close as possible to reference data obtained in a real-world radio network experiment. An evolutionary optimization process was applied to find near optimal parameter values four these models. We describe the optimization process, the error function that guides it and discuss the results.