Positioning is an interesting and well researched topic in these days, which is used at several aspect of our life. As it known users could use the words GPS (Global Positioning System) as the synonim of positioning quite often, however there are lot of other positioning systems. These systems don’t work properly at indoor environment due to the lack of sign coverage recieved from satellites. Here is the question which we want to be answered: - What kind of system could well functioning indoor as we expect and what will be the reference points? There are many solutions for indoor positioning, but I’ll examine the WLAN based system where the reference points are the access points (APs). There is a significant influence between the accuracy of position estimating and the placement of APs. I worked out such methods which provide a nearly optional topology of APs beside the minimum of the estimating error. I had to keep in my mind that the optimalization algorithms are based on the fingerprint technique. This technique uses RSS (Received Signal Strength) vectors to identificate all the points on the RSS map. These vectors are used by the KNN (K-Nearest neighbour) algorithm which is a classifying algorithm and its object to select the nearest vector to the measured vector from the database. I chose MATLAB programming environment to work out a simulation can compare the effectiveness of my optimalization methods and even with the random-naive method. In the end of the thesis, after my conclusions I’m going to talk about the possibilities of the research and development for the close future.