Semi-Exhaustive Reduced-Complexity Recursive Block Decoding for MIMO Systems

In this work we propose a new recursive block decoding method for MIMO systems. A complexity reduction is obtained compared to existing methods by avoiding the exhaustive decoding on one block. We propose the use of a semi-exhaustive search using a list composed of the Maximum Likelihood (ML) solution and its neighborhoods. We show through error probability derivation that we can achieve the full diversity by fixing a judicious choice of the list size or equivalently a threshold metric. A desired diversity order can be obtained by changing the list size. Simulation results show the obtained performances and the complexity gain.