Adaptive CSI Prediction in Linear Multi-User MIMO Systems

In this paper, we discuss channel adaptation techniques in linear multi-user multiple-input multiple-output (MUMIMO) systems with imperfect Channel State Information (CSI) caused by limited feedback bandwidth and feedback channel delay. We assume that such systems will operate in environments, where channel characteristics constantly change due to the movement of mobile terminals. We consider an approach where the impact of delayed CSI is partially mitigated by channel prediction performed at the base station side. In this paper, we use a dictionary based predictor that operates on phrases consisting of indices of quantized channel state information. To address variations in channel characteristics, we propose an algorithm that adapts the prediction dictionary to the current channel state. We demonstrate the performance of our algorithms in broadcast MU-MIMO systems with and without CSI prediction operating on a channel with changing Doppler rates. The simulation results show that significant sum-rate gains are achievable for a practical range of feedback delays. The additional advantage of our proposed adaptive prediction algorithms is that they can be used with any type of CSI quantization implementations and contribute very little extra complexity to the base station.