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Since the maximum likelihood (ML) decoding for quasi-orthogonal
space-time block codes (QO-STBC) with inner and outer codes multipleinputmultiple-
output (MIMO) antenna systems results too complex when the
modulation order index and the number of receive antennas increases, an
efficient reduced complexity ML-based decoding scheme is proposed in this
contribution, aiming to reach promising QO-STBC coded MIMO system
throughput × complexity trade-off. Under high-order modulation indexes
(16 ≤ M)-QAM, 4 × nR antennas, with nR ≥ 1, this work proposes a reduced
cluster search ML decoder (RCS-ML) and compares the performancecomplexity
with the ML decoding approach. Numerical results have indicated
no degradation in performance and an increasing reduction in the complexity of
RCS-ML decoder when the modulation order increases, been 12.5% of ML
decoding complexity for 16-QAM, and <1% for 256-QAM.
CitationAbrao, T. [et al.]. Reduced cluster search ML decoding for QO-STBC M-QAM MIMO systems. "International Journal of Satellite Communications Policy and Management", 2011, vol. 1, núm. 1, p. 15-30.
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