Adaptive beamforming for cognitive radio based wireless communication systems.

In wireless communications, cognitive radios are mostly used technique, in this estimation of number of occupied channels is a problem in any signal processing, so direction of arrival is considered. In adaptive beamforming, least mean square algorithm is mostly used, but performance of algorithm decreases significantly due to fixed step size, so that it doesn't suit for signal to noise ratio variations. Variable step size based adaptive algorithm is proposed to improve performance. But this variable step size algorithm is computationally complex due to this reason its not preferred in practical applications. Therefore, in this paper robust variable step size adaptive algorithm is proposed for beamforming. By using sigmoid function, variable step size is obtained, using instantaneous mean error, sigmoid function is calculated then normalization done by squared sum of estimated signal power and instantaneous error. By this proposed algorithm, without tuning any parameter step size is updated adaptively, it performs well with low computational complexity, simulation results show better performance with proposed algorithm [ABSTRACT FROM AUTHOR]