Analysis and optimization of auto-correlation based frequency offset estimation

I. M. Ngebani; J. M. Chuma; S. Masupe

Analysis and optimization of auto-correlation based frequency offset estimation

I. M. Ngebani, J. M. Chuma, S. Masupe

Electrical, Computer & Telecommunications Engineering

Research output: Contribution to journal › Article › peer-review

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 (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.

Original language	English
Pages (from-to)	162-167
Number of pages	6
Journal	SAIEE Africa Research Journal
Volume	106
Issue number	3
Publication status	Published - Sep 1 2015

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Analysis and optimization of auto-correlation based frequency offset estimation'. Together they form a unique fingerprint.

Cite this

@article{5ad8a580ad76418d94b2c2c40f0efcf5,

title = "Analysis and optimization of auto-correlation based frequency offset estimation",

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 (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.",

author = "Ngebani, {I. M.} and Chuma, {J. M.} and S. Masupe",

year = "2015",

month = sep,

day = "1",

language = "English",

volume = "106",

pages = "162--167",

journal = "Transactions of the South African Institute of Electrical Engineers",

issn = "0038-2221",

publisher = "South African Institute of Electrical Engineers",

number = "3",

}

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

UR - http://www.scopus.com/inward/citedby.url?scp=84929312387&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84929312387

VL - 106

SP - 162

EP - 167

JO - Transactions of the South African Institute of Electrical Engineers

JF - Transactions of the South African Institute of Electrical Engineers

SN - 0038-2221

IS - 3

ER -