Nonlinear programming based detectors for multiuser systems

Aylin Yener

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publicationProceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages327-331
Number of pages5
ISBN (Electronic)0769510620, 9780769510620
DOIs
StatePublished - 2001
EventInternational Conference on Information Technology: Coding and Computing, ITCC 2001 - Las Vegas, United States
Duration: Apr 2 2001Apr 4 2001

Other

OtherInternational Conference on Information Technology: Coding and Computing, ITCC 2001
Country/TerritoryUnited States
CityLas Vegas
Period4/2/014/4/01

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

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