Blind equalization of constant modulus signals via restricted convex optimization

We formulate the blind equalization of constant modulus (CM) signals as a convex optimization problem. This is done by performing an algebraic transformation on the direct formulation of the equalization problem and then restricting the set of design variables to a subset of the original feasible set. In particular, we express the blind equalization problem as a linear objective function subject to some linear and semidefiniteness constraints. Such semidefinite programs (SDP) can be efficiently solved using interior point methods. Simulations indicate that our method performs better than the standard methods, whilst requiring significantly fewer data samples.