  This paper proposes a novel adaptive reduced-rank filtering scheme based on
the joint iterative optimization of adaptive filters. The proposed scheme
consists of a joint iterative optimization of a bank of full-rank adaptive
filters that constitutes the projection matrix and an adaptive reduced-rank
filter that operates at the output of the bank of filters. We describe minimum
mean-squared error (MMSE) expressions for the design of the projection matrix
and the reduced-rank filter and simple least-mean squares (LMS) adaptive
algorithms for its computationally efficient implementation. Simulation results
for a CDMA interference suppression application reveals that the proposed
scheme significantly outperforms the state-of-the-art reduced-rank schemes,
while requiring a significantly lower computational complexity.
