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

Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

202
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
202
Transmission Line Design Considerations01:23

Transmission Line Design Considerations

264
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...
264
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

264
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
264
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

886
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...
886
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

301
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
301
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

241
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
241

You might also read

Related Articles

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

Sort by
Same author

A Simulation Framework for Zoom-Aided Coverage Path Planning with UAV-Mounted PTZ Cameras.

Sensors (Basel, Switzerland)·2025
Same author

Securing UAV Flying Ad Hoc Wireless Networks: Authentication Development for Robust Communications.

Sensors (Basel, Switzerland)·2025
Same author

A Novel Network Pharmacology Strategy Based on the Universal Effectiveness-Common Mechanism of Medical Herbs Uncovers Therapeutic Targets in Traumatic Brain Injury.

Drug design, development and therapy·2024
Same author

Residue levels, processing factors and risk assessment of pesticides in ginger from market to table.

Journal of hazardous materials·2024
Same author

pH-Dependent Reversible Self-Assembly of β-Lactoglobulin-Derived Reducing Peptides.

Journal of agricultural and food chemistry·2024
Same author

Endoscopic Longitudinal Incision and Recanalization in the Treatment of Acquired Esophageal Atresia (with Video).

Digestive diseases and sciences·2024
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: Nov 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

10.1K

Efficient Allocation for Downlink Multi-Channel NOMA Systems Considering Complex Constraints.

Zhengjia Xu1, Ivan Petrunin1, Teng Li1

  • 1School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford MK43 0AL, UK.

Sensors (Basel, Switzerland)
|April 3, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces three heuristic algorithms for dynamic power and channel allocation in multi-channel non-orthogonal multiple access systems. GRASP and SSD algorithms significantly improve data rates, especially in spectrum-scarce environments.

Keywords:
NOMAgreedy policyheuristic solutionresource allocation

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

894
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.2K

Related Experiment Videos

Last Updated: Nov 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

10.1K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

894
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.2K

Area of Science:

  • Wireless Communication Systems
  • Optimization Algorithms
  • Resource Allocation

Background:

  • Downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems face challenges in efficient dynamic power and channel allocation (DPCA).
  • Practical constraints like sub-channel capacity, power budgets, minimum data rates, and priority control complicate allocation.
  • Existing methods may not optimally address these complex scenarios.

Purpose of the Study:

  • To develop and evaluate efficient heuristic algorithms for DPCA in MC-NOMA systems.
  • To compare the performance of stochastic, GRASP, and SSD algorithms under various system conditions.
  • To analyze the trade-offs between data rate, computational complexity, and resource utilization.

Main Methods:

  • Formulating DPCA as a combinatorial optimization problem.
  • Proposing three heuristic algorithms: stochastic, two-stage greedy randomized adaptive search (GRASP), and two-stage stochastic sample greedy (SSD).
  • Simulating and demonstrating algorithm performance with consideration for practical constraints.

Main Results:

  • The stochastic algorithm is effective in spectrum-dense environments with lower data rate demands.
  • GRASP and SSD achieve over six times higher data rates than the stochastic algorithm in spectrum-scarce environments with shorter running times.
  • SSD offers computational advantages over GRASP in systems with more channels, saving 66% running time with similar data rate outcomes.
  • GRASP outperforms SSG in terms of average data rate, variance, and time consumption when sub-channel numbers are small.

Conclusions:

  • Heuristic algorithms like GRASP and SSD provide significant performance improvements for DPCA in MC-NOMA systems.
  • Algorithm selection should consider the specific system environment, particularly spectrum availability and data rate requirements.
  • SSD presents a favorable balance of performance and computational efficiency for systems with ample channel resources.