TY - JOUR
T1 - Training sequence design for MIMO channels
T2 - An application-oriented approach
AU - Katselis, Dimitrios
AU - Rojas, Cristian R.
AU - Bengtsson, Mats
AU - Björnson, Emil
AU - Bombois, Xavier
AU - Shariati, Nafiseh
AU - Jansson, Magnus
AU - Hjalmarsson, Håkan
N1 - Publisher Copyright:
© 2013 Katselis et al.; licensee Springer.
PY - 2013/10/17
Y1 - 2013/10/17
N2 - In this paper, the problem of training optimization for estimating a multiple-input multiple-output (MIMO) flat fading channel in the presence of spatially and temporally correlated Gaussian noise is studied in an application-oriented setup. So far, the problem of MIMO channel estimation has mostly been treated within the context of minimizing the mean square error (MSE) of the channel estimate subject to various constraints, such as an upper bound on the available training energy. We introduce a more general framework for the task of training sequence design in MIMO systems, which can treat not only the minimization of channel estimator’s MSE but also the optimization of a final performance metric of interest related to the use of the channel estimate in the communication system. First, we show that the proposed framework can be used to minimize the training energy budget subject to a quality constraint on the MSE of the channel estimator. A deterministic version of the ‘dual’ problem is also provided. We then focus on four specific applications, where the training sequence can be optimized with respect to the classical channel estimation MSE, a weighted channel estimation MSE and the MSE of the equalization error due to the use of an equalizer at the receiver or an appropriate linear precoder at the transmitter. In this way, the intended use of the channel estimate is explicitly accounted for. The superiority of the proposed designs over existing methods is demonstrated via numerical simulations.
AB - In this paper, the problem of training optimization for estimating a multiple-input multiple-output (MIMO) flat fading channel in the presence of spatially and temporally correlated Gaussian noise is studied in an application-oriented setup. So far, the problem of MIMO channel estimation has mostly been treated within the context of minimizing the mean square error (MSE) of the channel estimate subject to various constraints, such as an upper bound on the available training energy. We introduce a more general framework for the task of training sequence design in MIMO systems, which can treat not only the minimization of channel estimator’s MSE but also the optimization of a final performance metric of interest related to the use of the channel estimate in the communication system. First, we show that the proposed framework can be used to minimize the training energy budget subject to a quality constraint on the MSE of the channel estimator. A deterministic version of the ‘dual’ problem is also provided. We then focus on four specific applications, where the training sequence can be optimized with respect to the classical channel estimation MSE, a weighted channel estimation MSE and the MSE of the equalization error due to the use of an equalizer at the receiver or an appropriate linear precoder at the transmitter. In this way, the intended use of the channel estimate is explicitly accounted for. The superiority of the proposed designs over existing methods is demonstrated via numerical simulations.
UR - http://www.scopus.com/inward/record.url?scp=84905245508&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905245508&partnerID=8YFLogxK
U2 - 10.1186/1687-1499-2013-245
DO - 10.1186/1687-1499-2013-245
M3 - Article
AN - SCOPUS:84905245508
VL - 2013
JO - Eurasip Journal on Wireless Communications and Networking
JF - Eurasip Journal on Wireless Communications and Networking
SN - 1687-1472
IS - 1
ER -