Generalized MMSE detection techniques for multipoint-to-point systems

We propose a receiver for multipoint-to-point systems based on the minimum mean square error (MMSE) criterion, where the symbols are detected in groups and already detected symbols are fed back for interference subtraction, as known for decision feedback equalization (DFE). The proposed scaled DFE (SDFE) has two special cases: 1) DFE for a group size of one, i.e., for symbol-by-symbol detection. 2) Maximum likelihood detection (MLD), if the group comprises all transmitted symbols. The diversity order of SDFE lies between the poor diversity order of DFE and the full diversity order of MLD. Therefore, SDFE offers a trade-off between complexity due to the group-wise symbol detection and the increased diversity order compared to DFE. We also present an algorithm to compute the SDFE filters with an order of complexity which is the same as that to compute linear equalization filters. Motivated by the promising results of detectors based on lattice reduction (LR), we combine SDFE with LR. The resulting detector exhibits full diversity order and improved performance compared to LR-DFE. The simulations show that SDFE is an interesting generalization of DFE for detectors with zero-forcing constraint, since SDFE even outperforms LR-DFE for realistic signal-to-noiseratio (SNR). However, LR-DFE exhibits the best results for an affordable complexity, when dropping the zero-forcing constraint.