Reconfigurable antenna based doa estimation and localization in cognitive radios: Low complexity algorithms and practical measurements

This paper addresses low-complexity algorithms and evaluates the practical performance of low-complexity primary user (PU) direction of arrival (DoA) estimation and PU localization with real world indoor measurement data. More specifically, we use a type of reconfigurable antenna known as leaky-wave antennas to sense the spatial distribution of the PU signal power. By deploying a very low-complexity algorithm, called MaxE, the secondary user (SU) sensors are then able to estimate their respective PU DoAs. Finally, a central fusion center combines the DoAs into a PU location estimate. The results of the practical measurements reveal that it is possible to implement a localization system with very low complexity and fairly good PU location capabilities in a cognitive radio network. Such PU localization capabilities can then be used, e.g. for enhanced PU interference management.