Signal detection in an impulsive noise environment using locally optimum detection

Arnab Roy; John F. Doherty

doi:10.1109/VETECF.2007.222

Signal detection in an impulsive noise environment using locally optimum detection

Arnab Roy, John F. Doherty

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

4 Scopus citations

Abstract

Locally optimum detection is a technique for reliable signal estimation in the presence of strong non-Gaussian interference. It is particularly suited to direct-spread spectrum systems due to the diversity gain achieved because of spreading. However, even more gains can possibly be derived by performing this operation in an iterative fashion, thereby allowing signal detection at even lower signal-to-interference ratios. In this paper the locally optimum detector used in an iterative scheme to suppress strong non-Gaussian interference is studied. The interference is modeled as Middleton class-A and the data stream is convolutionally encoded. Simulation results demonstrating performance improvement over a simple linear combiner are presented.

Original language	English (US)
Title of host publication	2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall
Pages	1022-1026
Number of pages	5
DOIs	https://doi.org/10.1109/VETECF.2007.222
State	Published - 2007
Event	2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall - Baltimore, MD, United States Duration: Sep 30 2007 → Oct 3 2007

Publication series

Name	IEEE Vehicular Technology Conference
ISSN (Print)	1550-2252

Other

Other	2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall
Country/Territory	United States
City	Baltimore, MD
Period	9/30/07 → 10/3/07

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering
Applied Mathematics

Access to Document

10.1109/VETECF.2007.222

Cite this

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title = "Signal detection in an impulsive noise environment using locally optimum detection",

abstract = "Locally optimum detection is a technique for reliable signal estimation in the presence of strong non-Gaussian interference. It is particularly suited to direct-spread spectrum systems due to the diversity gain achieved because of spreading. However, even more gains can possibly be derived by performing this operation in an iterative fashion, thereby allowing signal detection at even lower signal-to-interference ratios. In this paper the locally optimum detector used in an iterative scheme to suppress strong non-Gaussian interference is studied. The interference is modeled as Middleton class-A and the data stream is convolutionally encoded. Simulation results demonstrating performance improvement over a simple linear combiner are presented.",

author = "Arnab Roy and Doherty, {John F.}",

year = "2007",

doi = "10.1109/VETECF.2007.222",

language = "English (US)",

isbn = "1424402646",

series = "IEEE Vehicular Technology Conference",

pages = "1022--1026",

booktitle = "2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall",

note = "2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall ; Conference date: 30-09-2007 Through 03-10-2007",

}

Roy, A & Doherty, JF 2007, Signal detection in an impulsive noise environment using locally optimum detection. in 2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall., 4349871, IEEE Vehicular Technology Conference, pp. 1022-1026, 2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall, Baltimore, MD, United States, 9/30/07. https://doi.org/10.1109/VETECF.2007.222

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AU - Doherty, John F.

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Y1 - 2007

N2 - Locally optimum detection is a technique for reliable signal estimation in the presence of strong non-Gaussian interference. It is particularly suited to direct-spread spectrum systems due to the diversity gain achieved because of spreading. However, even more gains can possibly be derived by performing this operation in an iterative fashion, thereby allowing signal detection at even lower signal-to-interference ratios. In this paper the locally optimum detector used in an iterative scheme to suppress strong non-Gaussian interference is studied. The interference is modeled as Middleton class-A and the data stream is convolutionally encoded. Simulation results demonstrating performance improvement over a simple linear combiner are presented.

AB - Locally optimum detection is a technique for reliable signal estimation in the presence of strong non-Gaussian interference. It is particularly suited to direct-spread spectrum systems due to the diversity gain achieved because of spreading. However, even more gains can possibly be derived by performing this operation in an iterative fashion, thereby allowing signal detection at even lower signal-to-interference ratios. In this paper the locally optimum detector used in an iterative scheme to suppress strong non-Gaussian interference is studied. The interference is modeled as Middleton class-A and the data stream is convolutionally encoded. Simulation results demonstrating performance improvement over a simple linear combiner are presented.

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U2 - 10.1109/VETECF.2007.222

DO - 10.1109/VETECF.2007.222

M3 - Conference contribution

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SN - 9781424402649

T3 - IEEE Vehicular Technology Conference

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BT - 2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall

T2 - 2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall

Y2 - 30 September 2007 through 3 October 2007

ER -

Signal detection in an impulsive noise environment using locally optimum detection

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