On the performance of AoA estimation algorithms in cognitive radio networks

Bandwidth efficiency is very important parameter, because it relates to frequency spectrum, which is naturally, limited resource. The cognitive radio has been proposed as the future technology to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically to allow unlicensed access on non-interfering basis. Conventional sensing methods usually relate to sensing the spectrum in three dimensions viz. frequency, time and space. However, there are other dimensions `Angle' and `Code' that need to be explored further for spectrum opportunity. This paper investigates the performance of Angle of Arrival (AoA) estimation algorithms like Bartlett's, Capon, MUSIC, Root-MUSIC and ESPRIT in cognitive radio networks. 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 licensed user, improves frequency reuse capability and increases channel capacity by multiplexing multiple users (licensed and unlicensed) into the same channel at the same time in the same geographical area by forming the beam of unlicensed user in the direction other than the licensed users' AoA direction.