diff --git a/competition/tex/chapters/introduction.tex b/competition/tex/chapters/introduction.tex
index bc11756..fa9c389 100644
--- a/competition/tex/chapters/introduction.tex
+++ b/competition/tex/chapters/introduction.tex
@@ -55,19 +55,6 @@ where $\mObsVec_{1:t} = \mObsVec_{1}, \mObsVec_{1}, ..., \mObsVec_{t}$ is a seri
 The recursive density estimation of eq. \eqref{eq:recursiveDensity} is implemented using a particle-filter with the state transition as proposal density.
 This ensures valid position estimations even if a sensor is defect or is not provided by the smartphone itself.
 
-\section{Prior Arrangements}
-System setup is very easily and no fingerprinting is required.
-	\begin{figure}[h!]
-		\centering%
-		\includegraphics[trim=99 0 0 0, clip, width=8.2cm]{editor1.png}%
-	\end{figure}
-
-\begin{itemize}
-\item Map building: Grobe Beschreibung, Funktionen und Moeglichkeiten des Map Builders. bildchen
-\item Adding Transmitters: geht schnell und ist total einfach
-\end{itemize}
-
-
-
+\input{chapters/setup.tex}
 \input{chapters/components.tex}
 \input{chapters/performance.tex}
diff --git a/competition/tex/chapters/setup.tex b/competition/tex/chapters/setup.tex
new file mode 100644
index 0000000..14e3708
--- /dev/null
+++ b/competition/tex/chapters/setup.tex
@@ -0,0 +1,27 @@
+\section{Prior Arrangements}
+	
+	The main goal for our indoor navigation system was, to reduce the initial setup time as much as possible.
+	
+	As we do not rely on \docWIFI{} fingerprinting, no time consuming measurements are needed.
+	Instead, signal-strengths are predicted using a model, that needs the position
+	of each transmitter (\docAP{}, \docAPshort{}) within the building and three parameters.
+	For further simplification, those three parameters can be the same for all transmitters
+	and chosen empirically.
+	
+	The system's core is based on the building's floorplan which must be known beforehand.
+	Using an editor, developed especially for this purpose, the provided floorplan (PDF, Images, ..)
+	is used to (manually) derive a new data-structure that contains each of the building's floors including
+	its walls, doors, stairs and transmitters (see figure \ref{fig:mapEditor}). This step consumes most
+	of the setup time and might be (semi-)automated in the future.
+	
+	\begin{figure}
+		\centering%
+		\includegraphics[trim=99 0 0 0, clip, width=8.2cm]{editor1.png}%
+		\caption{One floor within a building, created by using our map-editor}
+		\label{fig:mapEditor}
+	\end{figure}
+	
+	The hereby created data-structure is used to derive a graph (automatically, offline),
+	that is transmitted to the smartphone (once per building)
+	and serves as base for the transition process (see \refeq{eq:recursiveDensity}),
+	modelling pedestrian walking behaviour and described within the next section.