Unconditional maximum likelihood approach for blind estimation of digital signals

In contrast to conventional array processing, in many applications, such as mobile communications, the concept of a parametric array manifold is ill defined. In mobile communications the loss of a well defined array manifold can be attributed to the complex propagation environment consisting of multiple local scatterers near the mobile and remote dominant scatterers, as well as other co-channel signals. In such applications, estimation methods developed in the conventional setting of array processing are of little use and blind estimation of the transmitted signals is of real importance. We present an unconditional maximum likelihood (UML) approach for blind estimation of multiple co-channel digital BPSK signals received by an antenna array, along with the array response matrix A. Based on the idea of fixed point iteration, an efficient algorithm is derived to obtain the UML estimate of A and the maximum a posteriori (MAP) estimates of the digital signals. Simulation results are presented to demonstrate the improved performance of the proposed UML method over the conventional conditional ML (CML) methods. An upper bound on the bit error rate is also presented