Abstract-In this paper, the performance of a multi-user multiple-input multiple-output (MIMO) system in time-varying channels is evaluated using measurement data. We consider the multi-user MIMO system using a block diagonalization (BD) scheme and an eigenbeam-space division multiplexing (E-SDM) technique. In an ideal case, the BD scheme eliminates inter-user interference, and the E-SDM technique suppresses inter-stream interference. In actual radio environments, however, channels change over time. This causes interference in the multi-user MIMO system even though the BD scheme and the E-SDM technique are used. To overcome this problem, the authors have developed a simple channel prediction scheme on the basis of a linear extrapolation and have demonstrated its effectiveness by computer simulations assuming the Jakes' model. To verify the performance of the channel prediction scheme in actual environments, we conducted a measurement campaign in indoor environments and measured a large amount of channel data. Using these data, we examined the channel transition and channel tracking with the prediction method. Then we obtained the biterror rate (BER) performance. The prediction technique was shown to track the channel and improve the BER performance almost to that in the ideal time invariant case.

SUMMARYAlthough multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

In the paper, performance of multiuser multipleinput multiple-output eigenbeam-space division multiplexing (E-SDM) systems in the downlink transmission is evaluated in both uncorrelated and correlated time-varying fading environments based on computer-generated data. In the ideal case, using the block diagonalization (BD) scheme, inter-user interference can be completely eliminated at each user; and using the E-SDM technique for each user, optimal resource can be allocated, and spatially orthogonal substreams can be obtained. In realistic environments, however, due to the dynamic nature of the channel and the processing delay at both the transmitter and the receiver, the channel change during the delay may cause existence of interuser interference even if the BD scheme is used. In addition, the change may also result in large inter-substream interference and no longer lead the allocated data resource for each user to the optimal condition. As a result, system performance may be degraded seriously. To overcome the problem, we propose a method of channel extrapolation to compensate for the channel change. Applying our proposed method, simulation results show that much better system performance can be obtained than the conventional case.

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