Abstract
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.
Original language | English (US) |
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Pages (from-to) | 3270-3275 |
Number of pages | 6 |
Journal | IEEE International Conference on Communications |
Volume | 6 |
State | Published - Aug 30 2004 |
Event | 2004 IEEE International Conference on Communications - Paris, France Duration: Jun 20 2004 → Jun 24 2004 |
Keywords
- Linear precoding
- Local maximum-likelihood
- MMSE
- OFDM