Matrix computations (3rd ed.)
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Convex Optimization
Transceiver design based on blockwise uniform channel decomposition for coded MIMO systems
IEEE Transactions on Wireless Communications
Regularized Channel Diagonalization for Multiuser MIMO Downlink Using a Modified MMSE Criterion
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Space-time bit-interleaved coded modulation for OFDM systems
IEEE Transactions on Signal Processing
Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels
IEEE Transactions on Signal Processing
Precoding in multiantenna and multiuser communications
IEEE Transactions on Wireless Communications
Generalized Design of Multi-User MIMO Precoding Matrices
IEEE Transactions on Wireless Communications
Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality
IEEE Transactions on Information Theory
Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels
IEEE Transactions on Information Theory
Sum power iterative water-filling for multi-antenna Gaussian broadcast channels
IEEE Transactions on Information Theory
Capacity and power allocation for fading MIMO channels with channel estimation error
IEEE Transactions on Information Theory
MIMO Broadcast Channels With Finite-Rate Feedback
IEEE Transactions on Information Theory
Tomlinson-Harashima Precoding for Broadcast Channels with Uncertainty
IEEE Journal on Selected Areas in Communications
Linear precoder designs for K-user interference channels
IEEE Transactions on Wireless Communications
Wireless Personal Communications: An International Journal
Multi-user Multi-stream Vector Perturbation Precoding
Wireless Personal Communications: An International Journal
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Block diagonalization (BD) is a well-known precoding method in multiuser multi-input multi-output (MIMO) broadcast channels. This scheme can be considered as a extension of the zero-forcing (ZF) channel inversion to the case where each receiver is equipped with multiple antennas. One of the limitation of the BD is that the sum rate does not grow linearly with the number of users and transmit antennas at low and medium signal-to-noise ratio regime, since the complete suppression of multi-user interference is achieved at the expense of noise enhancement. Also it performs poorly under imperfect channel state information. In this paper, we propose a generalized minimum mean-squared error (MMSE) channel inversion algorithm for users with multiple antennas to overcome the drawbacks of the BD for multiuser MIMO systems. We first introduce a generalized ZF channel inversion algorithm as a new approach of the conventional BD. Applying this idea to the MMSE channel inversion for identifying orthonormal basis vectors of the precoder, and employing the MMSE criterion for finding its combining matrix, the proposed scheme increases the signal-to-interference-plus-noise ratio at each user's receiver. Simulation results confirm that the proposed scheme exhibits a linear growth of the sum rate, as opposed to the BD scheme. For block fading channels with four transmit antennas, the proposed scheme provides a 3dB gain over the conventional BD scheme at 1 % frame error rate. Also, we present a modified precoding method for systems with channel estimation errors and show that the proposed algorithm is robust to channel estimation errors.