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Training sequence design for frequency offset and frequency-selective channel estimation
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DOI：10.1109/TCOMM.2003.819199.png)
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摘要
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We consider the problem of data-aided frequency-offset and channel estimation in the case of frequency-selective channels. More precisely, we address the problem of training sequence selection with the goal of providing accurate frequency offset and channel estimates. Toward this end, we consider the Cramer-Rao bound (CRB), for which we derive a closed-form expression. Since the CRB is a complicated function of the training sequence and the channel parameters, a much simpler asymptotic CRB is derived. Two criteria for training sequence design based on the asymptotic CRB are proposed, and a minmax approach is presented to optimize them. Our main contribution is to show that a white sequence is minmax optimal for both criteria considered, and that the quest for a generally optimal sequence is hardly motivated.
Keyword:
channel estimation
Cramer-Rao bound (CRB)
frequency offset estimation
frequency-selective channels
training sequence design
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期刊
IF:
8.3
论文数:
1.2W
被引数:
3.6W
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