Accession Number:

ADA422839

Title:

On Channel Estimation Using Superimposed Training and First-Order Statistics

Descriptive Note:

Journal article

Corporate Author:

AUBURN UNIV AL DEPT OF COMPUTER AND ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

2003-10-06

Pagination or Media Count:

4.0

Abstract:

Channel estimation for single-input multiple-output SIMO time-invariant channels is considered using only the first-order statistics of the data, A periodic nonrandom training sequence is added superimposed at a low power to the information sequence at the transmitter before modulation and transmission, Recently superimposed training has been used for channel estimation assuming no mean-value uncertainty at the receiver and using periodically inserted pilot symbols, We propose a different method that allows more general training sequences and explicitly exploits the underlying cyclostationary nature of the periodic training sequences, We also allow mean-value uncertainty at the receiver, Illustrative computer simulation examples are presented,

Subject Categories:

  • Statistics and Probability
  • Military Intelligence

Distribution Statement:

APPROVED FOR PUBLIC RELEASE