Adaptive blind widely linear CCM reduced-rank beamforming for large-scale antenna arrays

In this paper, we propose an adaptive blind reduced-rank beamforming algorithm based on Krylov-subspace (KS) techniques and widely linear (WL) processing for non-circular signals. In contrast to the conventional WL processing approach, the properties of the augmented covariance matrix are exploited to derive a new structured WL beamforming scheme based on the generalized sidelobe canceler (GSC) structure. We develop a recursive least square (RLS) algorithm according to the constrained constant modulus (CCM) criterion to update the reduced-rank beamformer so obtained. A detailed signal-to-interference-plus noise ratio (SINR) analysis and a computational complexity analysis are carried out. Simulation results show that the proposed algorithm outperforms its linear counterpart and the full-rank algorithms, achieving the best convergence performance among all the analyzed methods with a relatively low complexity.1