Development of blind algorithm with automatic gain control

Abstract

In this paper, the concept of blind algorithm with automatic gain control (AGC) is introduced in adaptive antenna system for signal optimization with an aim to estimate the desired response in adaptive fashion. Blind algorithm with AGC is a hybrid two-stage adaptive filtering algorithm; sequentially combining constant modulus algorithm (CMA) and Bessel least mean square (BLMS) algorithm. Blind Bessel beamformer with AGC does not require external reference signal to update its weight vectors and step size for convergence but updates itself from own reference signal obtained from the output of CMA. Similarly, step size is obtained from the correlation matrix which is the product of the signals induced in array elements of antenna. BLMS is the modified version of LMS algorithm; based on the non-uniform step size exploiting the asymptotic decay property of Bessel function of the first kind. The output of CMA provides input and reference signals for BLMS that makes it blind. The contributions of this paper include the development of novel blind theory concept and presentation of an AGC method in order to make the Bessel beamformer blind which can update itself electronically through the correlation matrix depending on the signal array vector with the aim to make the signal power constant.