Blind Regularized Constant Modulus Multiuser Detection via a Newton Algorithm

In code division multiple access systems, the objective function of the problem of blind linearly constrained constant modulus multiuser detection has multiple extreme points and slow convergence speed. To deal with this issue, we propose a regularized constant modulus multiuser detection approach with Newton algorithm. Specifically, we add a regularization term to the objective function to deal with the ill-posed problem. This ensures that the Hessian matrix of object function will remain positive definite, and achieve better performance. Then, we use the Lagrangian method to convert the regularized optimization problem with constants into an unconstrained one, and apply the Newton algorithm to obtain the solution. The simulation results show that the method can obtain a higher output signal-to-interference-plus-noise ratio, low bit error rate, and faster convergence speed than the existing methods, especially in the case of a low number of symbols.