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Related Concept Videos

Effects of feedback01:24

Effects of feedback

478
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
478
Feedback control systems01:26

Feedback control systems

256
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
256
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

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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...
67
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

73
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...
73
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

133
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
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PI Controller: Design01:24

PI Controller: Design

140
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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Feedback algorithms for intelligent reflecting surfaces: Phase shift matrix and single-bit feedback.

Sarmad Sohaib1, Muhammad Ahmad2, Muhammad Shafi3

  • 1Department of Electrical and Electronic Engineering, University of Jeddah, Jeddah, Saudi Arabia.

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|May 8, 2025
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Summary
This summary is machine-generated.

This study presents two feedback algorithms for intelligent reflecting surfaces (IRS). The single-bit feedback (SBF) algorithm offers superior performance in phase adjustment efficiency compared to the phase shift matrix (PSM) method.

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Area of Science:

  • Wireless Communications
  • Metamaterials
  • Signal Processing

Background:

  • Intelligent Reflecting Surfaces (IRS) are gaining traction for enhancing wireless communication efficiency.
  • Optimizing phase adjustments in IRS is crucial for maximizing signal-to-noise ratio (SNR).
  • Existing methods for IRS phase adjustment can be complex and computationally intensive.

Purpose of the Study:

  • To introduce and compare two novel feedback algorithms for IRS phase adjustment: Phase Shift Matrix (PSM)-based and Single-Bit Feedback (SBF)-based.
  • To evaluate the efficiency of these algorithms in improving IRS performance.
  • To determine which algorithm yields better results in terms of average bit error rate.

Main Methods:

  • Developed a PSM-based algorithm where the IRS phase shift vector is selected from a predefined matrix to maximize receiver SNR.
  • Introduced an SBF-based algorithm involving iterative random phase alterations and binary feedback from the receiver to the transmitter.
  • Conducted simulations to compare the average bit error rate performance of both algorithms.

Main Results:

  • The SBF-based algorithm demonstrated superior performance compared to the PSM-based algorithm.
  • SBF-based phase adjustment of IRS elements proved more effective in optimizing signal transmission.
  • Simulation results indicated a lower average bit error rate with the SBF approach.

Conclusions:

  • The SBF-based feedback algorithm is a more efficient method for phase adjustment in IRS systems.
  • This research highlights the potential of SBF for practical implementation in future wireless networks.
  • The findings suggest that SBF can significantly improve the overall performance of IRS-assisted communication systems.