Maximum likelihood detection of random primary networks for cognitive radio systems

Sunyoung Lee, Kae Won Choi, Seong Lyun Kim

Research output: Contribution to journalArticle

Abstract

In this letter, we focus on detecting a random primary user (PU) network for cognitive radio systems in a cooperative manner by using maximum likelihood (ML) detection. Different from traditional PU network models, the random PU network model in this letter considers the randomness in the PU network topology, and so is better suited for describing the infrastructure-less PU network such as an ad hoc network. Since the joint pdf required for the ML detection is hard to obtain in a closed form, we derive approximate ones from the Gaussian approximation. The performance of the proposed algorithm is comparable to the optimal one.

Original languageEnglish
Pages (from-to)3365-3369
Number of pages5
JournalIEICE Transactions on Communications
VolumeE95-B
Issue number10
DOIs
Publication statusPublished - 2012 Jan 1

Fingerprint

Radio systems
Cognitive radio
Maximum likelihood
Ad hoc networks
Topology

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

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Maximum likelihood detection of random primary networks for cognitive radio systems. / Lee, Sunyoung; Choi, Kae Won; Kim, Seong Lyun.

In: IEICE Transactions on Communications, Vol. E95-B, No. 10, 01.01.2012, p. 3365-3369.

Research output: Contribution to journalArticle

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