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Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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Resource Allocation and Sharing Methodologies When Reconfigurable Intelligent Surfaces Meet Multiple Base Stations.

Yoghitha Ramamoorthi1, Riku Ohmiya1, Masashi Iwabuchi1

  • 1NTT Access Network Service Systems Laboratories, Nippon Telegraph and Telephone Corporation, Yokosuka 239-0847, Japan.

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Summary

This study introduces Reconfigurable Intelligent Surface (RIS) sharing for 6G millimeter-wave (mmWave) networks. RIS sharing mechanisms significantly boost network throughput, offering an energy-efficient solution for enhanced wireless communication coverage.

Keywords:
6GRIS elementsreconfigurable intelligent surface (RIS)resource allocationschedulingsharingtime

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Area of Science:

  • Wireless Communication Systems
  • Electromagnetics and Signal Processing

Background:

  • 6G wireless systems aim for superior capacity, reliability, and energy efficiency over current cellular networks.
  • Millimeter-wave (mmWave) frequencies provide high capacity but suffer from significant attenuation and blockage.
  • Reconfigurable Intelligent Surfaces (RIS) can mitigate mmWave propagation challenges by intelligently controlling the wireless channel.

Purpose of the Study:

  • To address the issue of high RIS density in mmWave networks by proposing RIS sharing mechanisms.
  • To optimize resource allocation for RIS sharing, considering both time and RIS elements.
  • To evaluate the performance of RIS sharing against existing systems.

Main Methods:

  • Formulation of RIS sharing resource allocation as an optimization problem.
  • Development of heuristic algorithms to solve the time and element-based RIS sharing problems.
  • Detailed simulations to compare proposed methods with benchmark and non-sharing RIS systems.

Main Results:

  • Proposed time-based RIS sharing improved throughput by up to 53% in specific scenarios.
  • Proposed element-based RIS sharing improved throughput by up to 25% in specific scenarios.
  • RIS sharing demonstrated significant performance gains compared to systems without sharing.

Conclusions:

  • RIS sharing is a viable and effective strategy for enhancing 6G mmWave network performance.
  • The proposed heuristic methods provide efficient solutions for resource allocation in RIS sharing.
  • RIS sharing offers a scalable and energy-efficient approach to expand coverage in challenging wireless environments.