The term smart-home has become very popular over the last years, gaining a great deal of importance in technological fields of research, especially in the field of Ambient Assisted Living (AAL). AAL represents an important branch of the Human Computer Interaction (HCI) research and focuses on supporting older and disabled persons in their everyday life. For disabled persons, for instance people in wheelchairs, the smart-home can offer increased support and an overall better experience in everyday life. Further, non-disabled persons could also benefit from the smart-home experience with many supportive functions for day to day living. The smart-home field of research covers a wide area of technological topics, one of these is location inference. Location plays an integral role in smart-home environments, thus many functions and actions depend on the user's current location in the home. For outdoor environments robust solutions like the American GPS for navigation systems, aGPS for smart-phones, or the European Galileo already exist. For indoor-environments such as smart-homes, only a few useable technologies are available. For high-resolution location inference i.e. high precision of the estimated current location, only expensive and complicated solutions are available. On the other hand, inexpensive approaches lead to only a rough location determination (low precision), thus not practicable for the smart-home purpose, where a high precision is required.