  In this paper, we propose a novel adaptive reduced-rank strategy for very
large multiuser multi-input multi-output (MIMO) systems. The proposed
reduced-rank scheme is based on the concept of joint iterative optimization
(JIO) of filters according to the minimization of the bit error rate (BER) cost
function. The proposed optimization technique adjusts the weights of a
projection matrix and a reduced-rank filter jointly. We develop stochastic
gradient (SG) algorithms for their adaptive implementation and introduce a
novel automatic rank selection method based on the BER criterion. Simulation
results for multiuser MIMO systems show that the proposed adaptive algorithms
significantly outperform existing schemes.
