Adaptive multi-antenna systems based on self-growing symmetric radial basis function

We propose a self-growing strategy to improve the learning speed of the symmetric radial basis function (SRBF) beamformer for multi-antenna systems. This novel beamforming scheme is designed based on a geometric relationship between the hidden nodes of SRBF and the current array outputs. The center vectors of this novel scheme can be quickly and properly initialized, so the fast learning can be achieved. We have shown that, under a short training sequence, bit-error rates are greatly improved, even when the number of center vectors is really huge.