TY - JOUR
T1 - Maximally robust 2-d channel estimation for OFDM systems
AU - Nisar, Muhammad Danish
AU - Utschick, Wolfgang
AU - Hindelang, Thomas
N1 - Funding Information:
Manuscript received June 03, 2009; accepted January 13, 2010. Date of publication February 17, 2010; date of current version May 14, 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Milica Stojanovic. The work of M. Danish Nisar was supported by Nokia Siemens Networks GmbH & Co. KG, Munich, Germany.
PY - 2010/6
Y1 - 2010/6
N2 - Two-dimensional minimum mean square error (MMSE) channel estimation for orthogonal frequency division multiplexing (OFDM) systems is known to perform better than the least squares, as well as the conventional 1-D MMSE estimation, owing to its ability of exploiting both, the time and the frequency correlations among the channel frequency response (CFR) coefficients. Its superior performance comes however at the price of increased requirementsthe knowledge of observation noise power and that of the channel frequency, as well as time correlation functions. In practical transmission scenarios, where channel correlation functions are not known or cannot be easily estimated, it is desirable to have an estimator that is robust to mismatches between the assumed and the actual channel correlation function. While such a robust estimator, for the case of an infinite number of observations, is well known for various uncertainty classes, not much attention has been paid to the practical case of a finite number of observations. We derive in this paper, the maximally robust (MR) 2-D channel estimator for the case of a finite number of pilot observations under some realistic constraints on the uncertainty class to which the 2-D channel correlation sequence belongs. We demonstrate that the correlation sequence associated with the MR estimator can be obtained by a simple semi-definite optimization procedure and is interestingly different from the well-known heuristic proposals. Simulation results establish the superiority of the proposed MR estimator over commonly employed heuristic robust estimator by as much as 3 dB in terms of the worst-case estimation MSE and around 1 dB in terms of the average BER performance under different practical transmission scenarios of interest.
AB - Two-dimensional minimum mean square error (MMSE) channel estimation for orthogonal frequency division multiplexing (OFDM) systems is known to perform better than the least squares, as well as the conventional 1-D MMSE estimation, owing to its ability of exploiting both, the time and the frequency correlations among the channel frequency response (CFR) coefficients. Its superior performance comes however at the price of increased requirementsthe knowledge of observation noise power and that of the channel frequency, as well as time correlation functions. In practical transmission scenarios, where channel correlation functions are not known or cannot be easily estimated, it is desirable to have an estimator that is robust to mismatches between the assumed and the actual channel correlation function. While such a robust estimator, for the case of an infinite number of observations, is well known for various uncertainty classes, not much attention has been paid to the practical case of a finite number of observations. We derive in this paper, the maximally robust (MR) 2-D channel estimator for the case of a finite number of pilot observations under some realistic constraints on the uncertainty class to which the 2-D channel correlation sequence belongs. We demonstrate that the correlation sequence associated with the MR estimator can be obtained by a simple semi-definite optimization procedure and is interestingly different from the well-known heuristic proposals. Simulation results establish the superiority of the proposed MR estimator over commonly employed heuristic robust estimator by as much as 3 dB in terms of the worst-case estimation MSE and around 1 dB in terms of the average BER performance under different practical transmission scenarios of interest.
KW - Channel estimation
KW - Minimax optimization
KW - Multicarrier systems
KW - Orthogonal frequency division multiplexing (OFDM) systems
KW - Robust signal processing
KW - Worst-case estimation
UR - http://www.scopus.com/inward/record.url?scp=77952574723&partnerID=8YFLogxK
U2 - 10.1109/TSP.2010.2043126
DO - 10.1109/TSP.2010.2043126
M3 - Article
AN - SCOPUS:77952574723
SN - 1053-587X
VL - 58
SP - 3163
EP - 3172
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 6
M1 - 5411747
ER -