Performance analysis of angle of arrival estimation algorithms for dynamic spectrum access in cognitive radio networks

The cognitive radio has been proposed to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically to secondary users on non-interfering basis. But, the conventional spectrum sensing methods seek for spectrum opportunities in either of three dimensions viz. time, frequency and space. However, other dimensions like `Code´ and `Angle´ need to be exploited further for spectrum opportunity. This paper investigates the performance of Angle-of-Arrival (AoA) estimation algorithms like Capon, MUSIC, and ESPRIT in cognitive radio networks. In order to improve the performance of AoA algorithms, the new technique known as `adaptive thresholding´ has been proposed. The performance of the algorithms has been evaluated in AWGN and time varying fading channels. The results show that the performance of the algorithms improves with increasing number of array elements, increasing number of snapshots and increasing signal to-noise ratio. This new approach of AoA estimation of primary user improves frequency reuse capability by multiplexing primary and secondary users into the same channel at the same time in the same geographical area by forming the beam of secondary user in the direction other than the primary users´ AoA direction.