Neural Blind Beamformers for Multi-Users

New neural blind beamformer for multi-users are presented in this paper. The weighting vectors of beamformers can be estimated blindly by minimizing a new cost function based on least-squares constant modulus algorithm so as to separate the multi-users and find the direction. At the same time, a developed neural network is used to compute the inverse of a matrix, which not only improve the computing speed but also use easily hardware to carry out the blind beamforming. The performance of the new beamformers is analyzed with computer simulation.