TY - JOUR
T1 - Analysis and optimization of auto-correlation based frequency offset estimation
AU - Ngebani, I. M.
AU - Chuma, J. M.
AU - Masupe, S.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - 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 (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.
AB - 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 (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.
UR - http://www.scopus.com/inward/record.url?scp=84929312387&partnerID=8YFLogxK
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U2 - 10.23919/saiee.2015.8531942
DO - 10.23919/saiee.2015.8531942
M3 - Article
AN - SCOPUS:84929312387
SN - 0038-2221
VL - 106
SP - 162
EP - 167
JO - SAIEE Africa Research Journal
JF - SAIEE Africa Research Journal
IS - 3
ER -