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A MIMO decoding algorithm utilizing polydiagonalization and tail-biting trellis is proposed. Linear MIMO decoding, such as zero-forcing equalization, is a channel diagonalization technique, where all interferences from other data streams are suppressed for separate decoding. It is well known, however, that such decoders suffer from the noise enhancement. In the proposed scheme, interferences are partially allowed, in order to alleviate the noise enhancement and, then, post trellis decoding is used for the joint detection utilizing the poly-diagonal structure of the effective channel. Under the proposed framework, the zero-forcing equalizer can be regarded as special cases of poly-diagonalization, i.e., of the first order. And the proposed scheme can provide a tradeoff between the complexity and performance by choosing an appropriate order of poly-diagonalization. According to the simulation results, considerable gain can be obtained even with the second order, i.e., bi-diagonalization, for which the decoding complexity is far less than that of the maximum likelihood decoding.

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In this paper, we propose an efficient low complexity MIMO detection method for double space-frequency transmit diversity (D-SFTD) based coded OFDM system. The proposed MIMO detector involves three-step filtering process to efficiently de-correlate spatially-multiplexed and space-frequency-coded signals without direct matrix inversion process. As the proposed MIMO detector takes advantage of frequency selectivity, not a favorable channel condition for SFBC system, performance degradation caused by low correlation between two consecutive subcarriers is compensated by assigning weighting factor per subcarrier. From computer simulation results, our scheme in D-SFTD outperforms previously proposed suboptimal MIMO detection methods such as iterative interference cancellation based V-BLAST.

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