Topics in matrix analysis
Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Statistical eigenmode transmission over jointly correlated MIMO channels
IEEE Transactions on Information Theory
Optimum linear joint transmit-receive processing for MIMO channels with QoS constraints
IEEE Transactions on Signal Processing
Deconstructing multiantenna fading channels
IEEE Transactions on Signal Processing
Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals
IEEE Transactions on Signal Processing
A generalized space-time multiple-input multiple-output (MIMO) channel model
IEEE Transactions on Wireless Communications
Optimal training for MIMO frequency-selective fading channels
IEEE Transactions on Wireless Communications
Model-based channel estimation framework for MIMO multicarrier communication systems
IEEE Transactions on Wireless Communications
A stochastic MIMO channel model with joint correlation of both link ends
IEEE Transactions on Wireless Communications
MIMO channel modeling and the principle of maximum entropy
IEEE Transactions on Information Theory
Correlated MIMO wireless channels: capacity, optimal signaling, and asymptotics
IEEE Transactions on Information Theory
A space-time correlation model for multielement antenna systems in mobile fading channels
IEEE Journal on Selected Areas in Communications
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This paper presents two analytic correlated multiple-input multiple-output (MIMO) block fading channel models and their time-variant extensions that encompass the popular Kronecker model and the more general Weichselberger model as special cases. Both static and time-variant models offer compact representations of spatial- and/or time-correlated channels. When the transmit antenna array is such that the associated MIMO channel has a small angle spread (AS), which occurs quite often in a cellular downlink, our models admit reduced-rank channel representations. They also provide compact channel state information (CSI) descriptions which are needed in feedback systems and in many post channel estimation applications. The latter has the important implication of reduced feedback channel bandwidth requirement and lower post-processing complexity. Based on one of the proposed channel models we present novel iterative algorithms for estimating static and time-variant MIMO channels. The proposed models make it natural to decompose each iteration of our algorithms into two successive stages that are responsible for estimating the correlation coefficients and the signal direction, respectively. Using popular industry-approved standard channel models, we verify through simulations that our algorithms yield good MSE performance which, in many practical cases, is better than that achievable by a conventional leastsquare estimator. The mean-squared error (MSE) performance of our estimators are analyzed and the resulting predictions are consistent with those estimated by simulations.