Fastest-Known Maximum-Likelihood Decoding of Quasi-Orthogonal STBCs with QAM Signals

We present a maximum-likelihood (ML) decoder with the lowest computational complexity known to-date for full-diversity, arbitrary size Quasi-Orthogonal Space-Time Block Codes (QO-STBCs) with symbols from square or rectangular quadrature amplitude modulation (QAM) constellations. We start with the formulation of an explicit joint two-complex-symbol decoder for general QO-STBCs with arbitrary complex symbols and then derive the proposed ML decoder for QO-STBCs with QAM symbols. The complexity savings are made possible by a simplified quadratic ML decoding statistic that utilizes algebraically the structure of the signal points of the QAM constellation. Comparative computational complexity analysis with existing ML implementations and simulation studies are included herein for illustration and validation purposes.