Channel estimation and user-wise symbol detection for space-time coding system

Space-time coding (STC) techniques, which combine antenna array signal processing and channel coding techniques, are very promising approaches to substantial increase in capacity in the wireless communications channels. The goal of the system is to exploit this capacity in a practical way. In this paper we consider maximum a posteriori (MAP) channel estimation and Maximum Likelihood (ML) approach for detecting the symbols for all the users in an iterative fashion. Symbols are detected user-wise, considering the rest of the symbols as interfering symbols. The symbols of interferers are modeled as discrete priors. In this case in which the finite alphabet gets exploited for the multiple access interference (MAI) symbols, a simplification for the posterior MAI symbol probabilities is introduced based on Mean Field Theory. Simulations show that our (reduced complexity) method give very close performance to exact ML.