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AuthorSalman T.
AuthorBadawy A.
AuthorElfouly T.M.
AuthorMohamed A.
AuthorKhattab T.
Available date2022-04-21T08:58:29Z
Publication Date2015
Publication NameIWCMC 2015 - 11th International Wireless Communications and Mobile Computing Conference
AbstractEstimating the number of sources received by an antenna array have been well known and investigated since the starting of array signal processing. Accurate estimation of such parameter is critical in many applications that involve prior knowledge of the number of received signals. Information theoretic approaches such as Akaikes information criterion (AIC) and minimum description length (MDL) have been used extensively even though they are complex and show bad performance at some stages. In this paper, a new algorithm for estimating the number of sources is presented. This algorithm exploits the estimated eigenvalues of the auto correlation coefficient matrix rather than the auto covariance matrix, which is conventionally used, to estimate the number of sources. We propose to use either of a two simply estimated decision statistics, which are the moving increment and moving standard deviation as metric to estimate the number of sources. Then process a simple calculation of the increment or standard deviation of eigenvalues to find the number of sources at the location of the maximum value. Results showed that our proposed algorithms have a better performance in comparison to the popular and more computationally expensive AIC and MDL at low SNR values and low number of collected samples. 2015 IEEE.
SponsorQatar National Research Fund
PublisherInstitute of Electrical and Electronics Engineers Inc.
Antenna arrays
Covariance matrix
Eigenvalues and eigenfunctions
Information theory
Mobile computing
Signal processing
Signal to noise ratio
Wireless telecommunication systems
Information criterion
Minimum description length
moving increment
Number of sources
Standard deviation
Matrix algebra
TitleEstimating the number of sources: An efficient maximization approach
TypeConference Paper

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