Nonlinear programming based detectors for multiuser systems

Aylin Yener

doi:10.1109/ITCC.2001.918815

Nonlinear programming based detectors for multiuser systems

Aylin Yener

Electrical Engineering

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

Abstract

Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.

Original language	English (US)
Title of host publication	Proceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	327-331
Number of pages	5
ISBN (Electronic)	0769510620, 9780769510620
DOIs	https://doi.org/10.1109/ITCC.2001.918815
State	Published - 2001
Event	International Conference on Information Technology: Coding and Computing, ITCC 2001 - Las Vegas, United States Duration: Apr 2 2001 → Apr 4 2001

Other

Other	International Conference on Information Technology: Coding and Computing, ITCC 2001
Country/Territory	United States
City	Las Vegas
Period	4/2/01 → 4/4/01

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Information Systems
Software

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10.1109/ITCC.2001.918815

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title = "Nonlinear programming based detectors for multiuser systems",

abstract = "Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.",

author = "Aylin Yener",

year = "2001",

doi = "10.1109/ITCC.2001.918815",

language = "English (US)",

pages = "327--331",

booktitle = "Proceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "International Conference on Information Technology: Coding and Computing, ITCC 2001 ; Conference date: 02-04-2001 Through 04-04-2001",

}

Yener, A 2001, Nonlinear programming based detectors for multiuser systems. in Proceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001., 918815, Institute of Electrical and Electronics Engineers Inc., pp. 327-331, International Conference on Information Technology: Coding and Computing, ITCC 2001, Las Vegas, United States, 4/2/01. https://doi.org/10.1109/ITCC.2001.918815

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T1 - Nonlinear programming based detectors for multiuser systems

AU - Yener, Aylin

PY - 2001

Y1 - 2001

N2 - Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.

AB - Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.

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U2 - 10.1109/ITCC.2001.918815

DO - 10.1109/ITCC.2001.918815

M3 - Conference contribution

AN - SCOPUS:84961784563

SP - 327

EP - 331

BT - Proceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - International Conference on Information Technology: Coding and Computing, ITCC 2001

Y2 - 2 April 2001 through 4 April 2001

ER -

Nonlinear programming based detectors for multiuser systems

Abstract

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All Science Journal Classification (ASJC) codes

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