The evolution of cellular technologies has been followed by a continuous increase in their capacity and complexity. As a consequence, network management has become a challenge for network operators, especially at indoor environments. In these scenarios the percentage of calls and traffic is much higher than outdoors. Hence, intelligent and automatic mechanisms for network operation and maintenance are deemed necessary, leading to the so-called Self-Organizing Networks (SON). SON mechanisms analyze network indicators like counters, alarms, etc. in order to improve the network performance. Furthermore, in indoor scenarios, the recent advances in indoor positioning systems allow the integration of terminal position in the definition of novel SON techniques. The availability of this additional information provides knowledge about terminal distributions, mobility patterns, etc., which is useful data to enhance the efficiency and performance of SON techniques. In this sense, this paper proposes and develops location-aware SON techniques for indoor femtocell networks. In particular, novel self-optimization and self-healing algorithms are defined, which are supported by an indoor cellular-positioning system. Such mechanisms are evaluated in a real testbed environment.