Low-complexity constant modulus algorithms for blind beamforming based on symmetrically distributed arrays

A class of low-complexity constant modulus (CM) algorithms with real-valued coefficients is proposed based on symmetrically distributed arrays (SDAs) by introducing a preprocessing transformation matrix. It is derived from the beamformer with a minimum mean square error (MSE) and three representative CMAs are studied including the basic CMA, least-squares CMA (LSCMA) and the recursive-least-squares CMA (RLSCMA). With the preprocessing matrix, the computational complexity of the overall system is reduced significantly; moreover, a faster convergence speed is achieved and given the same stepsize, the system arrives at a lower MSE. Simulation results are provided to verify the effectiveness of the proposed approach.