TY - JOUR
T1 - Everything you always wanted to know about training
T2 - Guidelines derived using the affine precoding framework and the CRB
AU - Vosoughi, Azadeh
AU - Scaglione, Anna
N1 - Funding Information:
Manuscript received October 27, 2004; revised March 26, 2005. This work is supported in part by the National Science Foundation under grant CCR-0133635. The material in this paper was presented in part at the 2003 IEEE Statistical Signal Processing Workshop and the 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Helmut Boelcskei.
PY - 2006/3
Y1 - 2006/3
N2 - In this paper, affine precoding is used to investigate the tradeoffs that exist while using the transmitter resources on training versus information symbols. The channel input is a training vector superimposed on a linearly precoded vector of symbols. A block-fading frequency-selective multi-input multi-output (MIMO) channel is considered. To highlight the tradeoffs between training and data symbols, the Fisher information matrix (FIM) is derived under two circumstances: the random parameter vector to be estimated contains 1) only fading channel coefficients and 2) unknown data symbols as well as the channel coefficients. While strategy 1 corresponds to the receiver structure in which the channel is estimated initially and the channel measurement is utilized to retrieve the data symbols, strategy 2 corresponds to the structure in which channel and symbol estimations are performed jointly. The interesting outcome of the study in this paper is that minimizing the channel Cramer-Rao bound (CRB) for strategies 1 and 2 under a total average transmit power constraint leads to different affine precoder design guidelines.
AB - In this paper, affine precoding is used to investigate the tradeoffs that exist while using the transmitter resources on training versus information symbols. The channel input is a training vector superimposed on a linearly precoded vector of symbols. A block-fading frequency-selective multi-input multi-output (MIMO) channel is considered. To highlight the tradeoffs between training and data symbols, the Fisher information matrix (FIM) is derived under two circumstances: the random parameter vector to be estimated contains 1) only fading channel coefficients and 2) unknown data symbols as well as the channel coefficients. While strategy 1 corresponds to the receiver structure in which the channel is estimated initially and the channel measurement is utilized to retrieve the data symbols, strategy 2 corresponds to the structure in which channel and symbol estimations are performed jointly. The interesting outcome of the study in this paper is that minimizing the channel Cramer-Rao bound (CRB) for strategies 1 and 2 under a total average transmit power constraint leads to different affine precoder design guidelines.
KW - Affine precoding
KW - Bayes estimator
KW - Block transmission
KW - Cramer-Rao bound (CRB)
KW - Fisher information matrix (FIM)
KW - Multi-input multi-output (MIMO) systems
KW - Mutual information
KW - Random parameter estimation
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U2 - 10.1109/TSP.2005.863031
DO - 10.1109/TSP.2005.863031
M3 - Article
AN - SCOPUS:33244476043
VL - 54
SP - 940
EP - 954
JO - IEEE Transactions on Acoustics, Speech, and Signal Processing
JF - IEEE Transactions on Acoustics, Speech, and Signal Processing
SN - 1053-587X
IS - 3
ER -