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The problem of symbol misidentification (SMI) for data-dependent superimposed training (DDST) is considered. The constraint conditions on the discrete Fourier transform matrix are derived and constellation rotation (CR) at the transmitter to avoid the SMI is proposed. Simulation results show that the DDST with CR can eliminate the symbol error floor and yield better detection performance than the original one.
References
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M. Ghogho ,
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E.A. Hernandez ,
A. Swami
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Channel estimation and symbol detection for block transmission using data-dependent superimposed training.
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1. Arriaga-Trejo, I.A., Orozco-Lugo, A.G., Veloz-Guerrero, A.: ‘Widely linear system estimation using superimposed training’, IEEE Trans. Signal Process, 2011, 59, (11), pp. 5651–5657 (doi: 10.1109/TSP.2011.2162834).
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2014.1681
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content/journals/10.1049/el.2014.1681
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Constellation rotation and symbol detection for data-dependent superimposed training