Title :
MMSE-based local ML detection of linearly precoded OFDM signals
Author :
Rugini, L. ; Banelli, P. ; Giannakis, G.B.
Author_Institution :
Dept. of Electr. & Inf. Eng., Perugia Univ., Italy
Abstract :
Linear precoding is a well known effective technique to boost the performance of orthogonal frequency-division multiplexing (OFDM) systems. A drawback of linearly precoded 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 nonnegligible performance loss with respect to the ML performance. This paper proposes 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.
Keywords :
OFDM modulation; Rayleigh channels; channel estimation; error statistics; least mean squares methods; maximum likelihood detection; multipath channels; LML detector; MMSE; OFDM system; channel diversity; linear minimum mean-squared error detection; linear precoding; local maximum-likelihood detection; orthogonal frequency-division multiplexing; Bit error rate; Computational complexity; Decision feedback equalizers; Detectors; Fading; Forward error correction; Frequency division multiplexing; OFDM; Performance gain; Performance loss;
Conference_Titel :
Communications, 2004 IEEE International Conference on
Print_ISBN :
0-7803-8533-0
DOI :
10.1109/ICC.2004.1313150