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
2015 IEEE International Conference on Digital Signal Processing (DSP)