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Analysis and optimization of auto-correlation based frequency offset estimation

dc.contributor.authorNgebani, I.M.
dc.contributor.authorChuma, Joseph Monamati
dc.contributor.authorMasupe, S.
dc.date.accessioned2023-02-14T10:38:58Z
dc.date.available2023-02-14T10:38:58Z
dc.date.issued2015-09
dc.description.abstractIn 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.description.accessibilityunrestricteden_US
dc.description.departmentcteen_US
dc.description.levelphden_US
dc.identifier.citationNgebani, 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.issn1991-1696
dc.identifier.urihttp://repository.biust.ac.bw/handle/123456789/542
dc.language.isoenen_US
dc.publisherSouth Africa Institute of Electrical Engineersen_US
dc.subjectAuto-correlationen_US
dc.subjectFrequency offset estimationen_US
dc.subjectOptimizationen_US
dc.subjectPerformance analysisen_US
dc.subjectUn-biased estimatoren_US
dc.titleAnalysis and optimization of auto-correlation based frequency offset estimationen_US

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