BLIND SIGNAL SEPARATION IN COMMUNICATIONS: MAKING USE OF KN OWN SIGNAL DISTRIBUTIONS

We apply maximum likelihood blind source separation [7] to complex valued signals mixed with complex valued nonstationary matrices. This case arises in radio communications with baseband signals. We incorporate known source signal distributions in the adaptation, thus making the algorithms less “blind”. This r esults in drastic reduction of the amount of data needed for successful convergence. Adaptation to rapidly changing signal mixing conditions, such as to fading in mobile communications, becomes now feasible as demonstrated by simulations in noisy conditions.