Performance Evaluation of a Joint Precoding and Channel Prediction scheme for Multiuser MIMO OFDM Systems in Time Varying Wireless Channel

Abstract

Multiple-input, multiple-output (MIMO) communications have attracted considerable attention in the last years. In particular, multiuser MIMO (MU MIMO) systems are able to offer higher link capacity of MIMO systems as long as channel state information (CSI) is available at the transmitter, so that the spatial properties of the channel can be exploited by precoding. However, the time varying nature of the channel may cause CSI to be outdated, thus degrading the overall performance of the system. Within this context, channel prediction can provide up-to-date channel CSI and reduce the performance loss. This paper presents a channel predictor based on the setmembership partial update affine projection (SM-PUAP) filtering as way to compensate the outdated CSI caused by the temporal variations of the communication channel in a multiuser MIMO OFDM (orthogonal frequency division multiplexing) system. A realistic standardized channel model is considered to evaluate the predictor and its influence on the broadcast channel of a multiuser MIMO scenario. The performance of the predictor is also compared to the well-known adaptive algorithm recursive least squares (RLS). Simulation results show that the SM-PUAP predictor has lower computational cost and superior performance when compared to the classical algorithm.