Estimators of the nakagami-m parameter and performance analysis

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

The Nakagami-m parameter is known to capture the envelope distribution of various fading channel conditions in wireless communications. The value of m is indicative of the severity of fading, and is a measure of channel quality, making its estimation necessary in many applications. In this paper, we summarize the existing estimators for the Nakagami-m parameter and propose a new class of estimators, whose performance is analyzed by deriving the asymptotic variance and comparing with the Cramer-Rao bound (CRB). Moreover, we develop a novel estimator robust to the presence of additive white Gaussian noise (AWGN) or any other additive noise with a symmetrical distribution. We also discuss practical issues not previously addressed in the literature including adaptation and computational complexity of these estimators. We conclude that our novel integer-moment based estimators are the best choice from a computational complexity and performance point of view. Simulation results corroborate our analysis.

Original languageEnglish (US)
Pages (from-to)519-527
Number of pages9
JournalIEEE Transactions on Wireless Communications
Volume4
Issue number2
DOIs
StatePublished - Mar 2005

Fingerprint

Performance Analysis
Computational complexity
Estimator
Cramer-Rao bounds
Additive noise
Fading channels
Computational Complexity
Cramér-Rao Bound
Robust Estimators
Communication
Asymptotic Variance
Additive Noise
Gaussian White Noise
Fading Channels
Fading
Wireless Communication
Envelope
Moment
Integer
Necessary

Keywords

  • Channel characterization
  • Parameter estimation

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Networks and Communications

Cite this

Estimators of the nakagami-m parameter and performance analysis. / Tepedelenlioglu, Cihan; Gao, Ping.

In: IEEE Transactions on Wireless Communications, Vol. 4, No. 2, 03.2005, p. 519-527.

Research output: Contribution to journalArticle

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