Elements of information theory
Elements of information theory
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Convex Optimization
Characterizing the statistical properties of mutual information in MIMO channels
IEEE Transactions on Signal Processing
Transmitter optimization and optimality of beamforming for multiple antenna systems
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Capacity-achieving input covariance for single-user multi-antenna channels
IEEE Transactions on Wireless Communications
Precoder Design Based on Correlation Matrices for MIMO Systems
IEEE Transactions on Wireless Communications
Space-time transmit precoding with imperfect feedback
IEEE Transactions on Information Theory
Capacity scaling in MIMO wireless systems under correlated fading
IEEE Transactions on Information Theory
On the capacity of spatially correlated MIMO Rayleigh-fading channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Impact of antenna correlation on the capacity of multiantenna channels
IEEE Transactions on Information Theory
General Capacity Bounds for Spatially Correlated Rician MIMO Channels
IEEE Transactions on Information Theory
High-SNR power offset in multiantenna communication
IEEE Transactions on Information Theory
On the Ergodic Capacity of Rank-1 Ricean-Fading MIMO Channels
IEEE Transactions on Information Theory
Capacity Performance of Polarized Distributed MIMO System on Rician Channel
Wireless Personal Communications: An International Journal
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With mean or covariance channel feedback, the input covariance matrix can be designed to achieve the ergodic capacity of a MIMO fading channel. It is known that the eigenvectors of the optimal input covariance matrix are the same as the eigen-vectors of the channel mean or covariance matrix. However, the optimal power allocation across the eigen-vectors is much less understood. In this paper, two scenarios are investigated: 1) Rician MIMO channels with mean channel feedback, and 2) Rayleigh MIMO channels with covariance channel feedback. We first derive a suboptimal power allocation algorithms in the spatial domain for expected mutual information maximization for two transmit antennas systems, based on an upper bound for the ergodic capacity of a MIMO channel with either channel mean or covariance information at the transmitter. Then, we extend heuristically the results to systems with multiple antennas at both the transmitter and receiver side. The proposed power allocation solution permits a closed-form expression and has a water-filling interpretation. Simulation results reveal that the proposed method performs nearly the same as the optimal solution (which requires highly complex optimization routines over random processes) with inappreciable difference.