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

Downsampling01:20

Downsampling

154
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
154
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

52
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
52
Upsampling01:22

Upsampling

231
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
231
The Maximum Power Transfer Theorem01:20

The Maximum Power Transfer Theorem

603
Consider a linear AC Thevenin equivalent circuit connected to a load impedance.
The load connected draws the current, and the circuit delivers the power to the load. The alternating current flowing through the load is determined using the rectangular form of voltages, currents, network impedance, and load impedance. The average power delivered to the load is obtained from the product of the square of current and load resistance.
603
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

284
Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured...
284
Beams with Symmetric Loadings01:15

Beams with Symmetric Loadings

186
The moment-area method is an analytical tool used in structural engineering to determine the slope and deflection of beams under various loads. Consider a cantilever with a concentrated load and moment at the free end. The first step is constructing a free-body diagram to calculate the reactions at the fixed end. Next, the bending moment diagram is plotted to visualize how the bending moment varies along the beam's length, focusing on points where the bending moment equals zero.
The M/EI...
186

You might also read

Related Articles

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

Sort by
Same author

Artificial plateau neurons with in-situ spike-malleability for rhythmic quadrupedal locomotion.

Nature communications·2026
Same author

Resonance Tuning of Localized Excitons via a Plasmonic Nanocavity.

ACS nano·2026
Same author

Eliminating Defect States in Monolayer Tungsten Diselenide by Coupling with a c-Plane Sapphire Surface.

Physical review letters·2025
Same author

2D Molybdenum Disulfide Embedded Photonic Crystal Fiber for all-Fiber Phase Retarder.

Advanced materials (Deerfield Beach, Fla.)·2025
Same author

Two-dimensional materials based two-transistor-two-resistor synaptic kernel for efficient neuromorphic computing.

Nature communications·2025
Same author

Nanofluidic Memristive Transition and Synaptic Emulation in Atomically Thin Pores.

Nano letters·2025
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

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

Related Experiment Video

Updated: Jun 27, 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

9.9K

Efficient Constant Envelope Precoding for Massive MU-MIMO Downlink via Majorization-Minimization Method.

Rui Liang1, Hui Li1, Yingli Dong1

  • 1School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China.

Entropy (Basel, Switzerland)
|April 26, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient constant envelope (CE) precoding algorithm for massive multi-user, multiple-input, multiple-output (MU-MIMO) systems. The novel algorithm improves energy efficiency and achieves a 1dB bit error rate gain over existing methods.

Keywords:
alternating minimizationconstant envelope precodingfast iterative shrinkage-thresholding methodmajorization-minimization methodsecond-order Taylor expansion

More Related Videos

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.7K
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K

Related Experiment Videos

Last Updated: Jun 27, 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

9.9K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

8.7K
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K

Area of Science:

  • Electrical Engineering
  • Wireless Communications
  • Signal Processing

Background:

  • Massive MU-MIMO systems require energy-efficient power amplifiers for practical base station implementation.
  • Constant envelope (CE) precoding enables the use of efficient nonlinear radio frequency amplifiers.

Purpose of the Study:

  • To develop an efficient CE precoding algorithm for massive MU-MIMO systems.
  • To optimize CE precoded signals and precoding factors for improved system performance.

Main Methods:

  • An alternating minimization (AltMin) framework is employed to optimize the CE precoded signal and precoding factor.
  • A combination of majorization-minimization (MM) and fast iterative shrinkage-thresholding (FISTA) methods is used for CE precoded signal optimization.
  • The algorithm incorporates channel characteristics and Taylor expansion for surrogate function construction.

Main Results:

  • The proposed CE precoding algorithm achieves approximately 1dB uncoded bit error rate (BER) performance gain compared to existing algorithms.
  • The algorithm demonstrates acceptable computational complexity.
  • The performance benefits extend to discrete constant envelope (DCE) precoding scenarios.

Conclusions:

  • The developed CE precoding algorithm offers significant performance improvements for massive MU-MIMO systems.
  • The algorithm is effective for both CE and DCE precoding, enhancing energy efficiency and reducing power consumption.