Proceedings of the 2006 international conference on Wireless communications and mobile computing
A diversity guarantee and SNR performance for unitary limited feedback MIMO systems
EURASIP Journal on Advances in Signal Processing
Feedback reduction in uplink MIMO OFDM systems by chunk optimization
EURASIP Journal on Advances in Signal Processing
Optimality of beamforming in fading MIMO multiple access channels
IEEE Transactions on Communications
Combining beamforming and space-time coding using noisy quantized feedback
IEEE Transactions on Communications
IEEE Transactions on Communications
Transmit equal gain precoding in Rayleigh fading channels
IEEE Transactions on Signal Processing
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
Robust QoS-constrained optimization of downlink multiuser MISO systems
IEEE Transactions on Signal Processing
Robust cognitive beamforming with partial channel state information
IEEE Transactions on Wireless Communications
Empirical comparison of MIMO and beamforming schemes for outdoor-indoor scenarios
IEEE Transactions on Wireless Communications
Network beamforming using relays with perfect channel information
IEEE Transactions on Information Theory
Statistical eigenmode transmission over jointly correlated MIMO channels
IEEE Transactions on Information Theory
IEEE Transactions on Signal Processing
Adaptive beamforming with dimension reduction in spatially correlated MISO channels
IEEE Transactions on Wireless Communications
Joint channel estimation and resource allocation for MIMO systems: part I: single-user analysis
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Capacity of a multiple-antenna fading channel with a quantized precoding matrix
IEEE Transactions on Information Theory
Optimizing training-based transmission for correlated MIMO systems with hybrid feedback
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Low SNR capacity of double-scattering MIMO channels with transmitter channel knowledge
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
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
IEEE Transactions on Information Theory
Maximum mutual information design for MIMO systems with imperfect channel knowledge
IEEE Transactions on Information Theory
Optimality of beamforming for MIMO multiple access channels via virtual representation
IEEE Transactions on Signal Processing
Near-optimal power allocation for MIMO channels with mean or covariance feedback
IEEE Transactions on Communications
Robust MMSE precoding in MIMO channels with pre-fixed receivers
IEEE Transactions on Signal Processing
On the robustness of transmit beamforming
IEEE Transactions on Signal Processing
Capacity of MIMO-MAC with transmit channel knowledge in the low SNR regime
IEEE Transactions on Wireless Communications
Asymptotic performance of MIMO wireless channels with limited feedback
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Computer Networks: The International Journal of Computer and Telecommunications Networking
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We solve the transmitter optimization problem and determine a necessary and sufficient condition under which beamforming achieves Shannon capacity in a linear narrowband point-to-point communication system employing multiple transmit and receive antennas with additive Gaussian noise. We assume that the receiver has perfect channel knowledge while the transmitter has only knowledge of either the mean or the covariance of the channel coefficients. The channel is modeled at the transmitter as a matrix of complex jointly Gaussian random variables with either a zero mean and a known covariance matrix (covariance information), or a nonzero mean and a white covariance matrix (mean information). For both cases, we develop a necessary and sufficient condition for when the Shannon capacity is achieved through beamforming; i.e., the channel can be treated like a scalar channel and one-dimensional codes can be used to achieve capacity. We also provide a waterpouring interpretation of our results and find that less channel uncertainty not only increases the system capacity but may also allow this higher capacity to be achieved with scalar codes which involves significantly less complexity in practice than vector coding.