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

Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

155
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
155
Errors in Global Positioning System01:26

Errors in Global Positioning System

126
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
126
Propagation Speed of Electromagnetic Waves01:30

Propagation Speed of Electromagnetic Waves

4.1K
Electromagnetic waves are consistent with Ampere's law. Assuming there is no conduction current Ampere's law is given as:
4.1K
Bandpass Sampling01:17

Bandpass Sampling

273
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
273
Transmission Line Design Considerations01:23

Transmission Line Design Considerations

222
Aluminum has become the material of choice for overhead transmission lines, surpassing copper due to its abundance and cost-effectiveness. The most prevalent type is the aluminum conductor, steel-reinforced (ACSR), which combines aluminum strands around a steel core. Other variants include all-aluminum conductors (AAC), all-aluminum alloy conductors (AAAC), aluminum conductor alloy-reinforced (ACAR), and aluminum-clad steel conductors. Advanced designs, such as aluminum conductors with steel...
222
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

144
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
144

You might also read

Related Articles

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

Sort by
Same author

A Lightweight Hybrid Authentication and Key Agreement Protocol for Decentralized Device-to-Device Communication with Post-Quantum Confidentiality.

Sensors (Basel, Switzerland)·2026
Same author

Overview of Embedded Rust Operating Systems and Frameworks.

Sensors (Basel, Switzerland)·2024
Same author

Trustworthy Environmental Monitoring Using Hardware-Assisted Security Mechanisms.

Sensors (Basel, Switzerland)·2024
Same author

Armed with Faster Crypto: Optimizing Elliptic Curve Cryptography for ARM Processors.

Sensors (Basel, Switzerland)·2024
Same author

Evaluation of 6LoWPAN Generic Header Compression in the Context of a RPL Network.

Sensors (Basel, Switzerland)·2024
Same author

Flexible and Efficient Security Framework for Many-to-Many Communication in a Publish/Subscribe Architecture.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 29, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K

Time-Slotted Spreading Factor Hopping for Mitigating Blind Spots in LoRa-Based Networks.

Alejandro Iglesias-Rivera1, Roald Van Glabbeek2,3, Erik Ortiz Guerra1

  • 1Departamento de Electrónica y Telecomunicaciones, Universidad Central "Marta Abreu" de Las Villas, Santa Clara 50100, Villa Clara, Cuba.

Sensors (Basel, Switzerland)
|March 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a time-slotted spreading factor hopping (TSSFH) mechanism to improve LoRaWAN network coverage by reducing blind spots. The relaying approach enhances packet delivery ratio but may increase device battery consumption.

Keywords:
IoTLoRa-basedblind spotsrandom scheduling

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

10.0K
Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.9K

Related Experiment Videos

Last Updated: Sep 29, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K
Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

10.0K
Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.9K

Area of Science:

  • Wireless communication networks
  • Internet of Things (IoT) connectivity
  • Radio frequency engineering

Background:

  • LoRaWAN (Long Range Wide Area Network) offers extended coverage but suffers from blind spots in traditional single-hop networks.
  • Existing multi-hop solutions often use fixed spreading factors (SF), neglecting the benefits of virtual channel orthogonality for mitigating coverage gaps.

Purpose of the Study:

  • To address blind spots and performance limitations in LoRaWAN networks.
  • To propose and evaluate a novel relaying approach utilizing time-slotted spreading factor hopping (TSSFH).
  • To leverage virtual channel orthogonality (frequency, SF) for improved network reliability.

Main Methods:

  • Implementation of a time-slotted spreading factor hopping (TSSFH) mechanism.
  • Integration of virtual channels and time slots into a unified frame structure.
  • Utilization of pseudo-random scheduling within network blind spots for simplified device communication.

Main Results:

  • Reduced packet collisions within blind spots due to increased communication opportunities.
  • Improved collision-free packet delivery ratio (PDR) with enhanced listening windows.
  • Demonstrated trade-off between improved PDR and increased end-device battery depletion.

Conclusions:

  • The proposed TSSFH mechanism effectively mitigates LoRaWAN blind spots and enhances packet delivery.
  • Pseudo-random scheduling within blind spots simplifies network organization and end-device communication.
  • Network performance gains are achieved at the cost of potentially higher energy consumption for end devices.