Non-data-aided signal-to-noise-ratio estimation

Ami Wiesel*, Jason Goldberg, Hagit Messer

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Non-data-aided (NDA) signal-to-noise-ratio (SNR) estimation is considered for binary phase shift keying systems where the data samples are governed by a normal mixture distribution. Inherent estimation accuracy limitations are examined via a simple, closed-form approximation to the associated Cramer-Rao Bound which eliminates the need for numerical integration. The Expectation-Maximization algorithm is proposed to iteratively maximize the NDA likelihood function. Simulation results show that the resulting estimator offers statistical efficiency over a wider range of scenarios than previously published methods.

Original languageEnglish
Pages (from-to)197-201
Number of pages5
JournalConference Record - International Conference on Communications
Volume1
StatePublished - 2002
Event2002 International Conference on Communications (ICC 2002) - New York, NY, United States
Duration: 28 Apr 20022 May 2002

Fingerprint

Dive into the research topics of 'Non-data-aided signal-to-noise-ratio estimation'. Together they form a unique fingerprint.

Cite this