A constrained version of fitting PDF algorithm for blind source separation

An adaptive multiuser constrained version of a fitting probability density function (PDF) algorithm (FPA) for source separation is proposed. The novel algorithm is derived from the multiuser kurtosis (MUK) procedure proposed in the literature. In fact, the proposed approach may be viewed as a generalization of the MUK one. The resulting algorithm is evaluated through computational simulations in the context of a space division multiple access (SDMA) system. The obtained results show that a better performance is attained with respect to the unconstrained version.