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Space-Time Block Coding for Wireless Communications
Space-Time Block Coding for Wireless Communications
Convex Optimization
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Statistical eigenmode transmission over jointly correlated MIMO channels
IEEE Transactions on Information Theory
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IEEE Transactions on Wireless Communications
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A stochastic MIMO channel model with joint correlation of both link ends
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Space-time block codes from orthogonal designs
IEEE Transactions on Information Theory
Space-time transmit precoding with imperfect feedback
IEEE Transactions on Information Theory
Combining beamforming and orthogonal space-time block coding
IEEE Transactions on Information Theory
Orthogonal designs with maximal rates
IEEE Transactions on Information Theory
Impact of antenna correlation on the capacity of multiantenna channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Efficient use of side information in multiple-antenna data transmission over fading channels
IEEE Journal on Selected Areas in Communications
A simple transmit diversity technique for wireless communications
IEEE Journal on Selected Areas in Communications
A stochastic MIMO radio channel model with experimental validation
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Multiple-input-multiple-output measurements and modeling in Manhattan
IEEE Journal on Selected Areas in Communications
Fading correlations in wireless MIMO communication systems
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Signal Processing
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The impact of transmission design and spatial correlation on the symbol error rate (SER) is analyzed for multi-antenna communication links. The receiver has perfect channel state information (CSI), while the transmitter has either statistical or no CSI. The transmission is based on orthogonal space-time block codes (OSTBCs) and linear precoding. The precoding strategy that minimizes the worst-case SER is derived for the case when the transmitter has no CSI. Based on this strategy, the intuitive result that spatial correlation degrades the SER performance is proved mathematically. In the case when the transmitter knows the channel statistics, the correlation matrix is assumed to be jointly-correlated (a generalization of the Kronecker model). The eigenvectors of the SER-optimal precoding matrix are shown to originate from the correlation matrix and the remaining power allocation is a convex problem. Equal power allocation is SER-optimal at high SNR. Beamforming is SER-optimal at low SNR, or for increasing constellation sizes, and its optimality range is characterized. A heuristic low-complexity power allocation is proposed and evaluated numerically. Finally, it is proved analytically that receive-side correlation always degrades the SER. Transmit-side correlation will however improve the SER at low to medium SNR, while its impact is negligible at high SNR.