TY - JOUR
T1 - MMSE-based local ML detection of linearly precoded OFDM signals
AU - Rugini, L.
AU - Banelli, P.
AU - Giannakis, G. B.
PY - 2004
Y1 - 2004
N2 - Linear precoding is a well known effective technique to boost the performance of orthogonal frequency-division multiplexing (OFDM) systems. A drawback of linearly preceded OFDM (LP-OFDM) systems is the high computational complexity required by maximum-likelihood (ML) detection, which is mandatory to capture all the channel diversity. Conversely, low-complexity techniques, such as the linear minimum mean-squared error (MMSE) detection, suffer from non-negligible performance loss with respect to the ML performance. In this paper, we propose a detection technique that performs a local ML (LML) search in the neighborhood of the output provided by the MMSE detector. The trade-off between performance and complexity of the proposed LML-MMSE detector, which fall between the ones of the MMSE and ML detectors, can be nicely adjusted by appropriately setting the neighborhood size. Simulation results show that the LML-MMSE detector with minimum neighborhood size outperforms a block decision-feedback equalization (DFE) approach, while preserving a similar complexity.
AB - Linear precoding is a well known effective technique to boost the performance of orthogonal frequency-division multiplexing (OFDM) systems. A drawback of linearly preceded OFDM (LP-OFDM) systems is the high computational complexity required by maximum-likelihood (ML) detection, which is mandatory to capture all the channel diversity. Conversely, low-complexity techniques, such as the linear minimum mean-squared error (MMSE) detection, suffer from non-negligible performance loss with respect to the ML performance. In this paper, we propose a detection technique that performs a local ML (LML) search in the neighborhood of the output provided by the MMSE detector. The trade-off between performance and complexity of the proposed LML-MMSE detector, which fall between the ones of the MMSE and ML detectors, can be nicely adjusted by appropriately setting the neighborhood size. Simulation results show that the LML-MMSE detector with minimum neighborhood size outperforms a block decision-feedback equalization (DFE) approach, while preserving a similar complexity.
KW - Linear precoding
KW - Local maximum-likelihood
KW - MMSE
KW - OFDM
UR - http://www.scopus.com/inward/record.url?scp=4143066056&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4143066056&partnerID=8YFLogxK
U2 - 10.1109/icc.2004.1313150
DO - 10.1109/icc.2004.1313150
M3 - Conference article
AN - SCOPUS:4143066056
SN - 0536-1486
VL - 6
SP - 3270
EP - 3275
JO - IEEE International Conference on Communications
JF - IEEE International Conference on Communications
T2 - 2004 IEEE International Conference on Communications
Y2 - 20 June 2004 through 24 June 2004
ER -