Combined blind equalization and classification of multiple signals

Barathram Ramkumar, Tamal Bose

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A multiuser automatic modulation classifier (MAMC) is an important component of a multiantenna cognitive radio (CR) receiver that helps the radio to better utilize the spectrum. MAMC identifies the modulation schemes of multiple users in a frequency band simultaneously. A multi-input-multi-output (MIMO) blind equalizer is another important component of a multiantenna CR receiver that improves symbol detection performance by reducing inter symbol interference (ISI) and inter user interference (IUI). In a CR scenario, it is preferable to also consider the performance of the automatic modulation classifier (AMC) while designing the blind equalizer. In this paper we propose a MIMO blind equalizer that improves the performance of both multiuser symbol detection and cumulant based MAMC.

Original languageEnglish (US)
Title of host publicationPECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems
Pages339-344
Number of pages6
StatePublished - Sep 12 2011
Externally publishedYes
Event1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011 - Vilamoura, Algarve, Portugal
Duration: Mar 5 2011Mar 7 2011

Publication series

NamePECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems

Other

Other1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011
CountryPortugal
CityVilamoura, Algarve
Period3/5/113/7/11

Keywords

  • Cumulants
  • MIMO blind equalizer
  • Multiuser automatic modulation classifier (MAMC)

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Communication

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  • Cite this

    Ramkumar, B., & Bose, T. (2011). Combined blind equalization and classification of multiple signals. In PECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems (pp. 339-344). (PECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems).