MIMO channel prediction results on outdoor collected data

In this paper we analyze the performance of an autoregressive MIMO channel predictor on outdoor data collected with both vehicular and pedestrian transmitter motion. The metric of performance considered is aggregate beamforming gain obtained using dominant eigenmode MIMO communications when the transmit beamforming vector is chosen based on the channel prediction. We show that while the prediction range obtained on this real data is somewhat less than earlier published results based on simulated data, we are still able to obtain 2X to 3X greater feedback latency tolerance than without using these predictive techniques.