1. |
- Digham, F, et al.
(author)
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Joint Pilot and Data Loading Technique for MIMO Systems Operating with Covariance Feedback
- 2004
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In: Fifth IEE International Conference on 3G Mobile Communication Technologies, 2004. 3G 2004.. - 0863413889 ; , s. 24-28
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Conference paper (peer-reviewed)abstract
- We consider a multiple input multiple output (MIMO) system wherein channel correlation as well as noisy channel estimation are both taken into account. For a given block fading duration, pilot-assisted channel estimation is carried out with the aid of a minimum mean square error estimator. The pilot sequences and data are jointly optimized to maximize the ergodic capacity while fulfilling a total transmit energy constraint. Using the optimization results, we study the effect of various system parameters and different types of channel knowledge. We show that systems with channel covariance knowledge and imperfect channel estimates can even outperform those with perfect channel estimation at the receiver, but without any channel knowledge at the transmitter. Further, we show that the signal to noise ratio and the block fading duration determine the qualitative behavior of ergodic capacity as a function of antenna spacing or angular spread. Finally, we find that the optimum pilot-to-data power ratio is always greater than one. It increases as the total transmit power decreases or as the block fading length increases.
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2. |
- Mehta, N B, et al.
(author)
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Rate of MIMO Systems with CSI at Transmitter and Receiver from Pilot-Aided Estimation
- 2004
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In: IEEE 60th Vehicular Technology Conference, VTC 2004-Fall.. - 1090-3038. - 0780385217 ; 3, s. 1575-1579
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Conference paper (peer-reviewed)abstract
- We consider realistic multiple input multiple output antenna systems operating over spatially colored channels with instantaneous, albeit imperfect, channel state information at the receiver and only covariance knowledge available at the transmitter. We focus on pilot-aided channel estimation in which the receiver uses minimum mean square error channel estimation. For such a setup, our goal is then to design both the pilot and data sequences optimally to maximize the information rates achievable over the channel. We first demonstrate that the estimation error cannot be modeled as additive white Gaussian noise. We adopt a lower bound on channel capacity with imperfect channel knowledge and show that an optimum design leads to a matching of the eigenspaces of the pilots and of the data to the eigenspace of the channel. Furthermore, the ranks of the pilot and data covariance matrices need to be equal, and the optimal training duration need only equal the above rank. The assignment of powers to the different modes of transmission can then be obtained numerically. The paper, in essence, extends the results in the literature that assume perfect channel knowledge at the receiver, and shows that fully exploiting covariance knowledge leads to a visible improvement in capacity when compared to schemes that assume no channel knowledge, whatsoever, at the transmitter.
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