A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

Multiple Input Multiple Output (MIMO) represents a highly promising technique for 4G communication networks as it uses multiple antennas at the transmitter and receiver to improve the reliability of transmissions and to provide a high data rate. This paper introduces an adjustable scheduling algorithm for multi-user MIMO systems that can provide an advantageous trade-off solution between throughput maximization and fair resource allocation among users. Specifically, our algorithm is proposed as a solution to system requirement issues through the flexible control of fairness factors.

In this paper we investigate designing optimal linear transmit/receive processing filters for multiuser MIMO downlinks with imperfect channel state information (CSI) and spatial fading correlation between antenna array at BS. A robust scheme is proposed to obtain the optimal linear transmit/receive filters in the sense of minimizing the average sum mean square error (SMSE) conditional on noisy channel estimates under a per-user transmit power constraint. Using an iterative procedure, the proposed scheme extends the existing optimization algorithm for uncorrelated single-user MIMO systems with perfect CSI to solve the problem of minimizing SMSE in spatially correlated MIMO downlinks with imperfect CSI. Comparing with non-robust scheme, we show that robust scheme efficiently mitigates the BER loss induced by imperfect CSI. In addition, the impact of fading correlation at BS on the performance of the proposed robust scheme is analyzed.

In time-varying channels, the channel state information available at the transmitter (CSIT) is outdated due to inherent time delay between the uplink channel estimation and the downlink data transmission in TDD systems. In this letter, we propose an iterative precoding method and a linear decoding method which are both based on minimum mean-squared error (MMSE) criteria to mitigate the interference among data streams and users created by outdated CSIT for multiuser MIMO downlink systems. Analysis and simulation results show that the proposed method can effectively reduce the impairment of the outdated CSIT and improve the system capacity.