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| Paper: | SPCOM-L3.1 |
| Session: | Superimposed training |
| Time: | Thursday, May 20, 09:30 - 09:50 |
| Presentation: |
Lecture |
| Topic: |
Signal Processing for Communications: Detection, Estimation, and Demodulation |
| Title: |
THE BEST TRAINING DEPENDS ON THE RECEIVER ARCHITECTURE |
| Authors: |
Azadeh Vosoughi; Cornell University | | |
| | Anna Scaglione; Cornell University | | |
| Abstract: |
We consider a block fading frequency selective multi-input multi-output (MIMO) channel in additive white Gaussian noise(AWGN). The channel input is a training vector superimposed on a linearly precoded vector of Gaussian symbols. This form of precoding is referred to as {\it affine precoding}. We derive theCramer-Rao bound (CRB) under two circumstances: the randomparameter vector to be estimated contains $(i)$ only fadingchannel coefficients, $(ii)$ unknown data symbols as well as thechannel coefficients. While case $(i)$ corresponds to the decoding schemes in which the channel is estimated first and the channel measurement is utilized to recover the data symbols, case $(ii)$ corresponds to methods in which channel and symbol estimation is performed jointly. The interesting outcome of our investigation is that minimizing trace of the channel CRB for cases $(i)$ and $(ii)$ under a total transmit power constraint leads to different affine precoder design guidelines. |
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