A qHLRT modulation classifier with antenna array and two-stage CFO estimation in fading channels

Hong Li; Yeheskel Bar-Ness; Ali Abdi; Wei Su

doi:10.1109/SARNOF.2006.4534799

A qHLRT modulation classifier with antenna array and two-stage CFO estimation in fading channels

Hong Li, Yeheskel Bar-Ness, Ali Abdi, Wei Su

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

A likelihood ratio test (LRT) -based modulation classifier is sensitive to unknown parameters, such as carrier frequency offset (CFO), phase shift, etc. To better handle this problem, a robust antenna array -based quasi-hybrid likelihood ratio test (qHLRT) approach is proposed in this paper. A nonmaximum likelihood (ML) estimator is employed to reduce the computational burden of multivariate maximization. A double CFO estimation scheme is also proposed, which increases the accuracy of CFO estimation. To deal with channel fading, maximal ratio combining approach is applied for CFO estimation as well as the computation of the likelihood functions. It is shown that when implementing with the nonlinear least-squares (NLS) phase parameters estimator and the method-of-moment (MoM) amplitude estimator, our scheme offers an effective way to recognize linear modulation formats with unknown parameters in fading channels.

Original language	English (US)
Title of host publication	2006 IEEE Sarnoff Symposium
DOIs	https://doi.org/10.1109/SARNOF.2006.4534799
State	Published - Dec 1 2006
Event	2006 IEEE Sarnoff Symposium - Princeton, NJ, United States Duration: Mar 27 2006 → Mar 28 2006

Other

Other	2006 IEEE Sarnoff Symposium
Country/Territory	United States
City	Princeton, NJ
Period	3/27/06 → 3/28/06

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Electrical and Electronic Engineering
Communication

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10.1109/SARNOF.2006.4534799

Cite this

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title = "A qHLRT modulation classifier with antenna array and two-stage CFO estimation in fading channels",

abstract = "A likelihood ratio test (LRT) -based modulation classifier is sensitive to unknown parameters, such as carrier frequency offset (CFO), phase shift, etc. To better handle this problem, a robust antenna array -based quasi-hybrid likelihood ratio test (qHLRT) approach is proposed in this paper. A nonmaximum likelihood (ML) estimator is employed to reduce the computational burden of multivariate maximization. A double CFO estimation scheme is also proposed, which increases the accuracy of CFO estimation. To deal with channel fading, maximal ratio combining approach is applied for CFO estimation as well as the computation of the likelihood functions. It is shown that when implementing with the nonlinear least-squares (NLS) phase parameters estimator and the method-of-moment (MoM) amplitude estimator, our scheme offers an effective way to recognize linear modulation formats with unknown parameters in fading channels.",

author = "Hong Li and Yeheskel Bar-Ness and Ali Abdi and Wei Su",

year = "2006",

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doi = "10.1109/SARNOF.2006.4534799",

language = "English (US)",

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booktitle = "2006 IEEE Sarnoff Symposium",

note = "2006 IEEE Sarnoff Symposium ; Conference date: 27-03-2006 Through 28-03-2006",

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T1 - A qHLRT modulation classifier with antenna array and two-stage CFO estimation in fading channels

AU - Li, Hong

AU - Bar-Ness, Yeheskel

AU - Abdi, Ali

AU - Su, Wei

PY - 2006/12/1

Y1 - 2006/12/1

N2 - A likelihood ratio test (LRT) -based modulation classifier is sensitive to unknown parameters, such as carrier frequency offset (CFO), phase shift, etc. To better handle this problem, a robust antenna array -based quasi-hybrid likelihood ratio test (qHLRT) approach is proposed in this paper. A nonmaximum likelihood (ML) estimator is employed to reduce the computational burden of multivariate maximization. A double CFO estimation scheme is also proposed, which increases the accuracy of CFO estimation. To deal with channel fading, maximal ratio combining approach is applied for CFO estimation as well as the computation of the likelihood functions. It is shown that when implementing with the nonlinear least-squares (NLS) phase parameters estimator and the method-of-moment (MoM) amplitude estimator, our scheme offers an effective way to recognize linear modulation formats with unknown parameters in fading channels.

AB - A likelihood ratio test (LRT) -based modulation classifier is sensitive to unknown parameters, such as carrier frequency offset (CFO), phase shift, etc. To better handle this problem, a robust antenna array -based quasi-hybrid likelihood ratio test (qHLRT) approach is proposed in this paper. A nonmaximum likelihood (ML) estimator is employed to reduce the computational burden of multivariate maximization. A double CFO estimation scheme is also proposed, which increases the accuracy of CFO estimation. To deal with channel fading, maximal ratio combining approach is applied for CFO estimation as well as the computation of the likelihood functions. It is shown that when implementing with the nonlinear least-squares (NLS) phase parameters estimator and the method-of-moment (MoM) amplitude estimator, our scheme offers an effective way to recognize linear modulation formats with unknown parameters in fading channels.

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DO - 10.1109/SARNOF.2006.4534799

M3 - Conference contribution

AN - SCOPUS:50649113510

SN - 1424400023

SN - 9781424400027

BT - 2006 IEEE Sarnoff Symposium

T2 - 2006 IEEE Sarnoff Symposium

Y2 - 27 March 2006 through 28 March 2006

ER -

A qHLRT modulation classifier with antenna array and two-stage CFO estimation in fading channels

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