The University of New Florida
The authors present a flexible class of stochastic models that are developed for cooperative wireless relay networks systems, in which the relay processing functionality is not known at the destination. The challenge is then to perform system identification in this wireless relay network. They first construct a statistical model based on a representation of the system using Gaussian Processes. They then develop a computationally efficient algorithm which is based on the Iterated Conditioning on the Modes estimation to undertake system identification for each relay in the presence of partial Channel State Information (CSI).