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Analysis and optimization of auto-correlation based frequency offset estimation

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dc.contributor.author Ngebani, I.M.
dc.contributor.author Chuma, Joseph Monamati
dc.contributor.author Masupe, S.
dc.date.accessioned 2023-02-14T10:38:58Z
dc.date.available 2023-02-14T10:38:58Z
dc.date.issued 2015-09
dc.identifier.citation Ngebani, I.M., Chuma, J. and Masupe, S. (2015) Analysis and optimization of auto-correlation based frequency offset estimation. SAIEE Africa Research Journal, 106, (3):162-168. doi: 10.23919/SAIEE.2015.8531942. en_US
dc.identifier.issn 1991-1696
dc.identifier.uri http://repository.biust.ac.bw/handle/123456789/542
dc.description.abstract In this letter, a general auto-correlation based frequency offset estimation (FOE) algorithm is analyzed. An approximate closed-form expression for the Mean Square Error (MSE) of the FOE is obtained, and it is proved that, given training symbols of fixed length N, choosing the number of summations in the auto-correlation to be 〈N/3〉 and the correlation distance to be 〈2N/3〉 is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization. en_US
dc.language.iso en en_US
dc.publisher South Africa Institute of Electrical Engineers en_US
dc.subject Auto-correlation en_US
dc.subject Frequency offset estimation en_US
dc.subject Optimization en_US
dc.subject Performance analysis en_US
dc.subject Un-biased estimator en_US
dc.title Analysis and optimization of auto-correlation based frequency offset estimation en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department cte en_US


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