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

Bandpass Sampling01:17

Bandpass Sampling

203
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....
203
Maximum Power Transfer01:16

Maximum Power Transfer

285
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...
285
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

1.1K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.1K
The Antenna Complex01:42

The Antenna Complex

6.0K
Plants and other photosynthetic organisms comprise pigments capable of absorption of direct sunlight. These pigments are present in the reaction center - the main site of photochemical reactions as well as in the antenna complex. Under average light conditions, the rate at which reaction center pigments absorb light is far below the electron transport chain's capacity. As a result, the reaction center alone cannot provide enough energy to drive photosynthesis. The photosynthetic efficiency...
6.0K
Construction of Frequency Distribution01:15

Construction of Frequency Distribution

7.8K
A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is...
7.8K
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

280
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
280

You might also read

Related Articles

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

Sort by
Same author

Safety and efficacy of liver transplantation for hepatocellular carcinoma with bile duct tumor thrombus: A single-arm, multicenter, prospective study.

Hepatobiliary & pancreatic diseases international : HBPD INT·2026
Same author

A Novel Demographic Indicator Fusion Network (DIFNet) for Dynamic Fusion of EEG and Demographic Indicators for Robust Depression Detection.

Sensors (Basel, Switzerland)·2025
Same author

Guideline on application of allogeneic vascular transplantation in abdominal surgery.

Hepatobiliary & pancreatic diseases international : HBPD INT·2025
Same author

Aromatic Volatile Substances in Different Types of Guangnan Dixu Tea Based on HS-SPME-GC-MS Odor Activity Value.

Metabolites·2025
Same author

Chinese guidelines for minimally invasive donor hepatectomy in living donor liver transplantation (2024 edition).

Hepatobiliary surgery and nutrition·2024
Same author

Mechanism of ginsenoside Rb<sub>3</sub> against OGD/R damage based on metabonomic and PCR array analyses.

Biomedical reports·2024

Related Experiment Video

Updated: Jul 16, 2025

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K

Spectrum Allocation and User Scheduling Based on Combinatorial Multi-Armed Bandit for 5G Massive MIMO.

Jian Dou1, Xuan Liu1, Shuang Qie1

  • 1China Electric Power Research Institute, Beijing 100192, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary

This study introduces a novel combinatorial multi-armed bandit (CMAB) approach for massive multiple-input multiple-output (MIMO) systems. The method enhances spectral efficiency by optimizing user scheduling and spectrum allocation while reducing pilot overhead.

Keywords:
massive MIMOmulti-armed banditspectrum allocationuser scheduling

More Related Videos

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.8K
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K

Related Experiment Videos

Last Updated: Jul 16, 2025

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.8K
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K

Area of Science:

  • Wireless Communication
  • Signal Processing
  • Information Theory

Background:

  • Massive MIMO is crucial for 5G, enhancing capacity and reducing latency.
  • Traditional methods often involve high pilot overhead and channel estimation burdens.
  • Optimizing user scheduling and spectrum allocation is key to maximizing spectral efficiency.

Purpose of the Study:

  • To propose a new user scheduling and spectrum allocation method for massive MIMO systems.
  • To reduce pilot overhead and improve spectral efficiency compared to existing techniques.
  • To leverage combinatorial multi-armed bandit (CMAB) for efficient resource management.

Main Methods:

  • A two-stage approach utilizing CMAB for user scheduling.
  • Employing a linear upper confidence bound (UCB) algorithm for arm selection.
  • Grouping statistical channel state information (CSI) for orthogonal subcarrier allocation.

Main Results:

  • The CMAB-based method avoids full channel estimation, significantly cutting pilot overhead.
  • The proposed user scheduling algorithm demonstrates logarithmic regret.
  • The two-stage method effectively reduces inter-user interference and boosts spectral efficiency.

Conclusions:

  • The CMAB-based user scheduling and spectrum allocation method offers a significant improvement for massive MIMO systems.
  • The approach achieves high spectral efficiency by minimizing pilot overhead and interference.
  • This method presents a promising direction for future 5G and beyond wireless networks.