Experimental Validation of the Performance of Channel Prediction Algorithms in MU-MIMO-OFDM Downlink System

In multi-user multiple input multiple output orthogonal frequency division multiplexing (MU- MIMO-OFDM) downlink system, it is important to have accurate channel state information (CSI) at the base station (BS) in order to minimize the inter-user interference (IUI). However when the channel changes rapidly, the available CSI at the BS can be outdated and this leads to the performance loss. The channel prediction algorithms can be used to predict the future CSI and compensate for the discrepancy between the estimated channel and the actual channel, and improve the performance of the overall system. In this paper, we propose to use recursive least square (RLS) algorithm to predict the CSI for the upcoming frame in MU-MIMO-OFDM downlink system. The simulation results show that RLS algorithm outperforms the other prediction algorithms such as normalized least mean square (NLMS) and the conventional linear extrapolation method. The simulation results are further validated with the measured channel results.