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Related Concept Videos

Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...

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Time Reduction for SLM OFDM PAPR Based on Adaptive Genetic Algorithm in 5G IoT Networks.

Esam A A Hagras1, Sameh F Desouky2, Saad Aldosary3

  • 1Faculty of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt.

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|December 9, 2023
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Summary

A new adaptive genetic algorithm (AGA) strategy significantly reduces peak-to-average power ratio (PAPR) by 3.87 dB and learning time by 95.56% in SLM-OFDM systems.

Keywords:
adaptive genetic algorithmpeak-to-average power ratioselected mapping

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Wireless Communications

Background:

  • Orthogonal Frequency Division Multiplexing (OFDM) systems suffer from high Peak-to-Average Power Ratio (PAPR).
  • Reducing PAPR is crucial for improving the power efficiency and performance of OFDM systems.
  • Existing methods like conventional genetic algorithm (GA) based Selective Mapping (SLM) offer improvements but have limitations in time efficiency and PAPR reduction.

Purpose of the Study:

  • To introduce a novel adaptive genetic algorithm (AGA) strategy for PAPR and time reduction in SLM-OFDM.
  • To evaluate the effectiveness of the proposed AGA-based SLM-OFDM technique compared to conventional SLM-OFDM and GA-SLM-OFDM.
  • To demonstrate significant improvements in both PAPR reduction and computational time.

Main Methods:

  • Implementation of a new Peak Average Power and Time Reduction (PAPTR) strategy utilizing an adaptive genetic algorithm (AGA).
  • Comparative simulations of the proposed AGA-SLM-OFDM against standard SLM-OFDM and conventional GA-SLM-OFDM.
  • Performance evaluation based on PAPR reduction and learning time metrics.

Main Results:

  • The AGA technique reduced PAPR by approximately 3.87 dB compared to standard SLM-OFDM.
  • A substantial learning time reduction of about 95.56% was achieved with AGA-SLM-OFDM versus traditional GA-SLM-OFDM.
  • The proposed AGA-SLM-OFDM showed a PAPR enhancement of around 3.87 dB over traditional OFDM.

Conclusions:

  • The proposed AGA strategy effectively enhances PAPR reduction in SLM-OFDM systems.
  • AGA significantly accelerates the learning time, making it more computationally efficient than GA-SLM-OFDM.
  • The AGA-based approach offers a promising solution for improving the efficiency of OFDM communication systems.