Multiple-input multiple-output least-squares constant modulus algorithms

We propose novel blind separation techniques for multiple-input multiple-output systems based on a least-squares constant modulus algorithm (LSCMA). To ensure that each output signal is extracted from different input signals, the proposed algorithms have been derived by using successive interference cancellation and the Gram-Schmidt orthogonalization procedure. The performance is observed through computer simulations and compared with the multitarget LSCMA (MT-LSCMA) and LS multiuser CMA (LS-MU-CMA). Simulation results have shown that the proposed algorithms exhibit better performance in terms of both bit error rate (BER) and convergence speed.