Fixed effort MIMO decoders for wireless indoor channels: Theory and practical field trials

We propose a fixed-effort MIMO decoder for frequency selective indoor channels that are characterized by strong line-of-sight (LOS) components. Contrarily to the maximum likelihood (ML) approach, where all possible hypotheses are investigated by the metrics calculation, the proposed MIMO detector performs the search over a reduced set of candidates. This search set contains a reduced but representative set of hypotheses around the linear solution obtained at the first detection stage. The candidates are selected according to pre-computed search probabilities. A decision feedback equalizer (DFE) is applied in order to remove the effect of the inter symbol interferences (ISI) caused by the channel dispersion. The method provides a near ML performance using a fixed computational effort determined by the hardware resources. The proposed detector also shows a significant complexity reduction compared to popular MIMO detectors such as the V-BLAST and the sphere decoder. Moreover, the proposed detector provides a soft output information for each transmitted bit, using the pre-selected candidates from the reduced search set which presents a promising aspect for the coded transmission.