Limits of multi-user MIMO systems using scheduling and rate feedback
Signal Processing
MIMO transceiver design via majorization theory
Foundations and Trends in Communications and Information Theory
Majorization and matrix-monotone functions in wireless communications
Foundations and Trends in Communications and Information Theory
Worst-case robust MIMO transmission with imperfect channel knowledge
IEEE Transactions on Signal Processing
Design guidelines for training-based MIMO systems with feedback
IEEE Transactions on Signal Processing
On rate-optimal MIMO signalling with mean and covariance feedback
IEEE Transactions on Wireless Communications
Statistical eigenmode transmission over jointly correlated MIMO channels
IEEE Transactions on Information Theory
Wireless Personal Communications: An International Journal
On the efficiency of directional antennas in MIMO communication systems
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
Optimizing training-based transmission for correlated MIMO systems with hybrid feedback
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Effective capacity maximization in multi-antenna channels with covariance feedback
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
IEEE Transactions on Signal Processing
Capacity of Correlated MISO Channels with Correlated Co-channel Interference and Noise
Wireless Personal Communications: An International Journal
On the robustness of transmit beamforming
IEEE Transactions on Signal Processing
Statistical precoding with decision feedback equalization over a correlated MIMO channel
IEEE Transactions on Signal Processing
Impact of spatial correlation and precoding design in OSTBC MIMO systems
IEEE Transactions on Wireless Communications
A majorization approach to downlink multiuser VBR video streaming
Computer Communications
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We study the optimal transmission strategy of a multiple-input single-output (MISO) wireless communication link. The receiver has perfect channel state information (CSI), while the transmitter has different types of CSI, i.e., either perfect CSI, or no CSI, or long-term knowledge of the channel covariance matrix. For the case in which the transmitter knows the channel covariance matrix, it was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvectors of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We derive a characterization of the optimum power allocation. Furthermore, we apply this result to provide an efficient algorithm which computes the optimum power allocation. In addition to this, we analyze the impact of correlation on the ergodic capacity of the MISO system with different CSI schemes. At first, we justify the belief that equal power allocation is optimal if the transmitter is uninformed and the transmit antennas are correlated. Next, we show that the ergodic capacity with perfect CSI and without CSI at the transmitter is Schur-concave, i.e., the more correlated the transmit antennas are, the less capacity is achievable. In addition, we show that the ergodic capacity with covariance knowledge at the transmitter is Schur-convex with respect to the correlation properties. These results completely characterize the impact of correlation on the ergodic capacity in MISO systems. Furthermore, the capacity loss or gain due to correlation is quantified. For no CSI and perfect CSI at the transmitter, the capacity loss due to correlation is bounded by some small constant, whereas the capacity gain due to correlation grows unbounded with the number of transmit antennas in the case in which transmitter knows the channel covariance matrix. Finally, we illustrate all theoretical results by numerical simulations.