Adaptive Minimum BER Reduced-Rank Interference Suppression Algorithms Based on Joint and Iterative Optimization of Parameters

In this letter, we propose a novel adaptive reducedrank strategy based on 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 subspace 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 direct-sequence code-division-multiple-access (DSCDMA) systems show that the proposed adaptive algorithms significantly outperform the existing schemes.