Blind (training-like) decoder assisted beamforming for DS-CDMA systems

We propose an iterative blind beamforming strategy for short-burst high-rate DS-CDMA systems. The blind strategy works by creating a set of "training sequences" in the receiver that is used as input to a semi-blind beamforming algorithm, thus producing a corresponding set of beamformers. The objective then becomes to find which beamformer gives the best performance (smallest bit error). Two challenges we face are: (1) to find a semi-blind algorithm that requires very few training symbols (to minimize the search time); (2) to find an appropriate criterion for picking the beamformer that offers the best performance. Different semi-blind algorithms and criteria are tested. The recently proposed SBCMACI (semi-blind CMA with channel identification) (Casella, I.R.S. et al., PIMRC, p.1972-6, 2002) is demonstrated to be ideal because of how few training symbols it needs for convergence. Of the tested criteria, one based on feedback from the decoder (essentially using trellis information) is shown to achieve nearly optimal performance.