Matrix analysis
Optimality of beamforming in fading MIMO multiple access channels
IEEE Transactions on Communications
IEEE Transactions on Wireless Communications
Transmit signal design for optimal estimation of correlated MIMO channels
IEEE Transactions on Signal Processing
Transmitter optimization and optimality of beamforming for multiple antenna systems
IEEE Transactions on Wireless Communications
Capacity of fading channels with channel side information
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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
How much training is needed in multiple-antenna wireless links?
IEEE Transactions on Information Theory
Capacity and power allocation for fading MIMO channels with channel estimation error
IEEE Transactions on Information Theory
Optimum Power Allocation for Single-User MIMO and Multi-User MIMO-MAC with Partial CSI
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Wireless Communications
Robust MMSE precoding in MIMO channels with pre-fixed receivers
IEEE Transactions on Signal Processing
Wireless Personal Communications: An International Journal
| Hi-index | 0.01 |
Multiple antenna systems are known to provide very large data rates, when the perfect channel state information (CSI) is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. We consider transmit-side correlated multi-input multi-output (MIMO) channels with block fading, where each block is divided into training and data transmission phases. The receiver has a noisy CSI that it obtains through a channel estimation process, while the transmitter has partial CSI in the form of covariance feedback. In Part I of this two-part paper, we consider the single-user case, and optimize the achievable rate jointly over parameters associated with the training phase and data transmission phase. In particular, we first choose the training signal to minimize the channel estimation error, and then, develop an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. Specifically, the algorithm finds the optimum training duration, the optimum allocation of power between training and data transmission phases, the optimum allocation of power over the antennas during the data transmission phase.