Semi-Blind Channel Estimation Using Superimposed Perfect Sequences for OFDM Systems
碩士 === 國立中山大學 === 通訊工程研究所 === 94 === A complex array for constructing perfect sequences is presented in this paper. The row sequences and their discrete Fourier transform form two sets of perfect sequences. The column sequences are orthogonal to each other for any cyclic shift. In addition, any comb...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/59304995356374082640 |
| Summary: | 碩士 === 國立中山大學 === 通訊工程研究所 === 94 === A complex array for constructing perfect sequences is presented in this paper. The row sequences and their discrete Fourier transform form two sets of perfect sequences. The column sequences are orthogonal to each other for any cyclic shift. In addition, any combination of the column sequences with complex weighting coefficients of equal amplitude is also a perfect sequence.
In addition, a superimposed training scheme is also proposed for channel estimation in OFDM systems. The perfect sequence is adopted since it has a constant magnitude in both the time domain and the frequency domain. Although the derived channel estimator has a slightly worse performance since the unknown data contributes extra noise, the effective data throughput is substantially increased. In addition, the proposed scheme is shown to have a much better peak-to-average power ratio (PAPR) because the added perfect sequence has a constant magnitude in the time domain.
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