Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

48.7K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
48.7K
Uncertainty: Overview00:59

Uncertainty: Overview

1.2K
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
1.2K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

7.5K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
7.5K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

97.7K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
97.7K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.1K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.1K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.3K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

System-Level Calibration of a Millimeter-Wave Vector Signal Analyzer with Uncertainties.

IEEE transactions on microwave theory and techniques·2026
Same author

Research training in clinical neuropsychology: the Iowa-Benton perspective.

Journal of clinical and experimental neuropsychology·2025
Same author

Millimeter-Wave Radio Channels vs. Synthetic Beamwidth.

IEEE communications magazine. IEEE Communications Society·2024
Same author

Correlation-Based Uncertainty in Loaded Reverberation Chambers.

IEEE transactions on electromagnetic compatibility·2024
Same author

Millimeter-wave Channel-Sounder Performance Verification using Vector Network Analyzer in a Controlled RF Channel.

IEEE transactions on antennas and propagation·2022
Same author

Influence of Noise on Scattering-Parameter Measurements.

IEEE transactions on microwave theory and techniques·2022
See all related articles

Related Experiment Video

Updated: Oct 28, 2025

Studying Cavitation Enhanced Therapy
07:36

Studying Cavitation Enhanced Therapy

Published on: April 9, 2021

5.5K

NB-IoT Devices in Reverberation Chambers: A Comprehensive Uncertainty Analysis.

Anouk Hubrechsen1, Kate A Remley2, Robert D Jones2

  • 1Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.

International Journal of Microwave and Wireless Technologies
|July 16, 2021
PubMed
Summary
This summary is machine-generated.

New internet-of-things (IoT) protocols like NB-IoT and CAT-M1 introduce significant measurement uncertainties in reverberation chambers. Current methods may overestimate uncertainty, potentially leading to non-compliance with standards.

Keywords:
CAT-M1Cellular TelecommunicationsChamber transfer functionInternet of ThingsNB-IoTReverberation chamberUncertaintyWireless System

More Related Videos

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

7.2K
Implementation of a Reference Interferometer for Nanodetection
16:11

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

9.5K

Related Experiment Videos

Last Updated: Oct 28, 2025

Studying Cavitation Enhanced Therapy
07:36

Studying Cavitation Enhanced Therapy

Published on: April 9, 2021

5.5K
Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

7.2K
Implementation of a Reference Interferometer for Nanodetection
16:11

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

9.5K

Area of Science:

  • Electromagnetic compatibility (EMC) testing
  • Wireless communication protocols
  • Metrology and measurement uncertainty

Background:

  • Narrowband Internet-of-Things (IoT) protocols (e.g., NB-IoT, CAT-M1) present unique challenges for reverberation chamber (RC) measurements.
  • These protocols' characteristics can lead to unaddressed measurement effects and increased channel variations, impacting uncertainty quantification.

Purpose of the Study:

  • To conduct a comprehensive uncertainty analysis for NB-IoT and CAT-M1 device measurements in RCs.
  • To identify and quantify dominant uncertainty components specific to these narrowband protocols.
  • To evaluate the impact of these uncertainties on compliance with existing standards.

Main Methods:

  • Extended a previous study on NB-IoT and CAT-M1 uncertainty in RCs.
  • Performed a detailed uncertainty analysis of reference and Device Under Test (DUT) measurement components.
  • Utilized significance testing to identify dominant uncertainty sources.

Main Results:

  • Certain uncertainty components are shown to be dominant for narrowband IoT protocols and cannot be neglected.
  • Standardized test methods may underestimate or misattribute uncertainty for these technologies.
  • Failure to account for these specific uncertainties can lead to significant overestimation and potential non-compliance.

Conclusions:

  • A refined uncertainty analysis is crucial for accurate NB-IoT and CAT-M1 measurements in reverberation chambers.
  • Current standardized testing procedures may require updates to accommodate narrowband IoT characteristics.
  • Accurate uncertainty quantification is essential for ensuring reliable device compliance.