TOA location estimation based on cognitive radio channel occupancy prediction

Spectrum, environment and location awareness capabilities play a vital role in the autonomous and adaptive characteristics of cognitive radio. Knowledge of a cognitive radio (CR) user´s location and type of environment may enhance optimisation of dynamic spectrum management and channel allocation. In this paper, a method for determining the near future location of a secondary user (SU) in a CR network, is proposed. This method incorporates a Time-of Arrival (TOA) location estimation algorithm with a Hidden Markhov Model (HMM) based channel occupancy prediction model. Using this method, location estimation under various channel conditions and for a range of available channel bandwidths, is investigated. Results indicate that non-line-of-sight conditions have a profoundly negative effect on location estimation accuracy, but that employing multiple future bandwidths as opposed to a single set of instantaneous bandwidths, does improve the situation, i.e. an average relative improvement in positional accuracy of 27%.