Data detection for MIMO OFDM systems with reduced complexity in a frequency selective environment

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In this work new fixed effort MIMO decoders for OFDM are proposed. Therefore the reduced search algorithms, performing the search over a reduced set of candidates based on pre-computed search set missing probabilities and other common detection algorithms for flat MIMO channels, are adapted to the OFDM system model. The new OFDM reduced search algorithms proposed are reaching near ML performance with much less computational effort by additionally considering the conditions of the different subchannel matrices during the selection of the candidates. Therefore the newly presented OFDM reduced search algorithms offer a higher flexibility reaching near ML performance with significantly reduced computational effort.