Optimal training sequence in MIMO systems with multiple interference sources

We address the problem of optimal training sequence design for MIMO systems over frequency flat fading channels in the presence of colored interference that is composed of the thermal noise and jamming signals transmitted by multiple jammers. We employ a training based channel estimation approach. During the training period, we obtain the information of the channel parameters by using a Bayesian (MMSE) channel estimator based on the received training block. We note that the mean square error (MSE) of the channel estimator depends on the choice of the training sequence set. We design the optimal training sequence set that minimizes the MSE of the channel estimator under a total transmit power constraint. In order to obtain the advantage of the optimal training sequence design, the transmitter requires long-term statistics of the interference correlation. Hence this information needs to be estimated at the receiver and fed back to the transmitter. We develop a feedback strategy that can reduce the estimation error of the short-term channel parameters with a minimal amount of information from the receiver.