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

Cable Subjected to a Distributed Load01:24

Cable Subjected to a Distributed Load

838
The analysis of suspension bridges is a complex and critical process that involves multiple factors, including the shape and tension of the main cables. The main cables of suspension bridges are subjected to distributed loads, which result in changes in tensile forces and deformation of the cable. These loads must be carefully considered to ensure that the bridge is safe and capable of supporting the weight of different loads.
838
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

813
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
813
Distributed Loads01:19

Distributed Loads

685
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
685
Circular Orbits and Critical Velocity for Satellites01:16

Circular Orbits and Critical Velocity for Satellites

3.1K
The Moon orbits around the Earth. In turn, the Earth (and other planets) orbit the Sun. The space directly above our atmosphere is filled with artificial satellites in orbit. One can examine the circular orbit, the simplest kind of orbit, to understand the relationship between the speed and the period of planets and satellites with respect to their positions and the bodies that they orbit.
Nicolaus Copernicus (1473-1543) first suggested that the Earth and all other planets orbit the Sun in...
3.1K
Maximum Power Transfer01:16

Maximum Power Transfer

484
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
484
Energy Stored In A Coaxial Cable01:31

Energy Stored In A Coaxial Cable

1.7K
A coaxial cable consists of a central copper conductor used for transmitting signals, followed by an insulator shield, a metallic braided mesh that prevents signal interference, and a plastic layer that encases the entire assembly.
In the simplest form, a coaxial cable can be represented by two long hollow concentric cylinders in which the current flows in opposite directions. The magnetic field inside and outside the coaxial cable is determined by using Ampère's law. The magnetic...
1.7K

You might also read

Related Articles

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

Sort by
Same author

QIMO: Q-Learning-Based Adaptive Impairment Margin Optimization in DVB-S2X Satellite Communication.

Sensors (Basel, Switzerland)·2026
Same author

Intra-Technology Enhancements for Multi-Service Multi-Priority Short-Range V2X Communication.

Sensors (Basel, Switzerland)·2025
Same author

Goats on the Move: Evaluating Machine Learning Models for Goat Activity Analysis Using Accelerometer Data.

Animals : an open access journal from MDPI·2024
Same author

Cardiac Arrhythmia Classification Using Advanced Deep Learning Techniques on Digitized ECG Datasets.

Sensors (Basel, Switzerland)·2024
Same author

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond.

Sensors (Basel, Switzerland)·2023
Same author

Coexistence Scheme for Uncoordinated LTE and WiFi Networks Using Experience Replay Based Q-Learning.

Sensors (Basel, Switzerland)·2021

Related Experiment Video

Updated: Oct 10, 2025

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

The CODYSUN Approach: A Novel Distributed Paradigm for Dynamic Spectrum Sharing in Satellite Communications.

Irfan Jabandžić1, Fadhil Firyaguna2, Spilios Giannoulis1

  • 1IDLab, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.

Sensors (Basel, Switzerland)
|December 10, 2021
PubMed
Summary

New distributed dynamic spectrum sharing (DSS) techniques enable efficient coexistence between satellite and terrestrial networks. These methods significantly improve spectrum utilization in Ka-band, outperforming static allocation.

Keywords:
distributed algorithmsdynamic spectrum sharingns-3satellite communicationsspectrum coexistence

More Related Videos

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K
Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
06:14

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

Published on: July 30, 2020

5.1K

Related Experiment Videos

Last Updated: Oct 10, 2025

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
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K
Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
06:14

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

Published on: July 30, 2020

5.1K

Area of Science:

  • Satellite Communications
  • Spectrum Management
  • Wireless Networking

Background:

  • Increasing satellite deployments necessitate flexible spectrum sharing.
  • Terrestrial services entering satellite bands accelerate the need for dynamic spectrum sharing (DSS).
  • Existing centralized DSS solutions face scalability challenges with growing satellite density.

Purpose of the Study:

  • To design distributed DSS techniques for efficient spectrum sharing between satellite and terrestrial networks.
  • To maximize spectrum utilization and minimize interference in shared frequency bands.
  • To evaluate DSS performance in key satellite communication use cases.

Main Methods:

  • Development of two distributed DSS techniques for satellite communications (SATCOM).
  • Analysis of opportunistic spectrum sharing in Ka-band for both downlink and uplink scenarios.
  • Performance comparison of proposed DSS techniques against static spectrum allocation.

Main Results:

  • Demonstrated notable performance gains using the proposed distributed DSS techniques.
  • Achieved enhanced spectrum utilization in selected Ka-band use cases.
  • Successfully supported coexistence between diverse satellite and terrestrial networks.

Conclusions:

  • Distributed DSS offers a scalable and efficient solution for future SATCOM spectrum sharing.
  • The proposed techniques effectively increase spectrum utilization and mitigate interference.
  • Dynamic and flexible spectrum sharing is crucial for accommodating increasing network demands.