A Unitary Transform Based Generalized Approximate Message Passing

We consider the problem of recovering an unknown signal from general nonlinear measurements obtained through a generalized linear model (GLM). Based on the unitary transform approximate message passing (UAMP) and expectation propagation, a unitary transform based generalized AMP (GUAMP) algorithm is proposed for general measurement matrices, in particular highly correlated matrices. Experimental results on quantized compressed sensing demonstrate that the proposed GUAMP significantly outperforms state-of-the-art Generalized AMP (AMP) and generalized vector AMP (GVAMP) under correlated matrices.