Reduced-Complexity Near-ML Detector for a Coded DSTTD-OFDM System

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概要

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• This letter introduces an efficient near-maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed near-ML detector constructs a candidate vector set through a relaxed minimization method. It reduces computational loads from $\mathcal{O}(2|\mathcal{A}|^{2})$ to $\mathcal{O}(|\mathcal{A}|^{2})$, where $|\mathcal{A}|$ is the modulation order. Numerical results indicate that the proposed near-ML detector provides both almost ML performance and considerable complexity savings.

• （社）電子情報通信学会の論文
• 2008-11-01

著者

• KIM Hyounkuk

  Information and Communications University (ICU)

• PARK Hyuncheol

  Information and Communications University (ICU)

• Kim Hyounkuk

  Information And Communications Univ. (icu) Daejeon Kor

• Park Hyuncheol

  Information And Communications Univ. (icu) Daejeon Kor

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• Improved Decision-Feedback Detection Schemes for STBC over Time-Selective Fading Channels
• Simplified Maximum-Likelihood Detection for a Coded DSTTD-OFDM System
• Reduced-Complexity Near-ML Detector for a Coded DSTTD-OFDM System

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