Adaptive reduced-rank constrained constant modulus beamforming algorithms based on joint iterative optimization of filters

This paper proposes a robust reduced-rank scheme and algorithms for adaptive beamforming based on joint iterative optimization (JIO) of adaptive filters. The scheme provides an efficient way to deal with filters with large number of elements. It consists of a bank of full-rank adaptive filters that forms a transformation matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. The transformation matrix projects the received vector onto a low-dimension vector, which is processed by the reduced-rank filter to estimate the desired signal. The expressions of the transformation matrix and the reduced-rank weight vector are derived according to the constrained constant modulus (CCM) criterion subject to different constraints. Two low-complexity adaptive algorithms are devised for the implementation of the proposed scheme with different constraints. Simulations are performed to show superior performance of the proposed algorithms in comparison with the existing methods.