Paper Title:
An Improved Channel Estimation Algorithm Based on Superimposed Training Sequence
  Abstract

A channel estimation algorithm based on superimposed training sequence is proposed in this paper. The algorithm does not need the allocation of time slot for superimposed training sequence, and it can estimate the channel coefficients without loss of bandwidth. The mean squared difference, Cramer-Rao bound and the lower bound of channel capacity are deduced based on the LS algorithm of channel estimation. It has simple structure, less computational requirement by using the LS algorithm. The result of simulation shows that the performance of system is improved to a large extent by using superimposed training sequence rather than direct training sequence, and the capacity of system is also increased.

  Info
Periodical
Advanced Materials Research (Volumes 179-180)
Edited by
Garry Zhu
Pages
482-489
DOI
10.4028/www.scientific.net/AMR.179-180.482
Citation
J. Yang, H. M. Zhang, W. Xie, "An Improved Channel Estimation Algorithm Based on Superimposed Training Sequence", Advanced Materials Research, Vols. 179-180, pp. 482-489, 2011
Online since
January 2011
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Price
$32.00
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