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Maximum Power Transfer01:16

Maximum Power Transfer

332
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...
332

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes.

Hibatallah Alwazani1, Anas Chaaban1

  • 1School of Engineering, University of British Columbia, Kelowna, BC V1V1V7, Canada.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary

Intelligent reflecting surfaces (IRS) enhance wireless sensor networks (WSN) by enabling low-power sensors. Opportunistic scheduling (OS) with IRS sensors shows promise for improved system throughput in various configurations.

Keywords:
intelligent reflecting surfacesmulti-user diversityopportunistic beamformingproportional fairnessround robinsystem outage probabilitywireless sensor networks

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Area of Science:

  • Wireless Communication
  • Sensor Networks
  • Metamaterials

Background:

  • Passive technologies like intelligent reflecting surfaces (IRS) offer low-cost, low-complexity enhancements for communication systems.
  • Wireless sensor networks (WSN) can benefit from IRS for reduced sensor power requirements and improved communication, particularly in applications like environmental monitoring.
  • Traditional WSNs often rely on active radio frequency (RF) electronics, which can be power-intensive.

Purpose of the Study:

  • To propose and analyze an IRS-equipped WSN architecture where sensors utilize IRSs instead of active RF components.
  • To investigate opportunistic scheduling (OS) for multi-sensor diversity in IRS-equipped WSNs, considering blind IRS operation.
  • To compare the performance of OS against round-robin (RR), proportional fairness (PF), and a theoretical upper bound.

Main Methods:

  • Development of an IRS sensor node (ISN) model that intercepts and modulates signals from a base station (BS).
  • Implementation and analysis of opportunistic scheduling (OS) algorithms for concurrent transmissions from multiple ISNs.
  • System-level simulations to evaluate average throughput based on the number of IRS elements (N) and ISNs (L).

Main Results:

  • Opportunistic scheduling (OS) demonstrates competitive performance compared to RR, PF, and the theoretical upper bound, especially under specific IRS and ISN configurations.
  • The study quantifies the impact of varying the number of IRS elements (N) and ISNs (L) on the average system throughput under OS.
  • Performance comparisons highlight scenarios where each scheduling scheme (OS, RR, PF) excels.

Conclusions:

  • IRS-equipped WSNs represent a viable and efficient approach for future low-power, high-performance wireless sensing.
  • Opportunistic scheduling is an effective strategy for managing transmissions in IRS-WSN environments, maximizing throughput.
  • The choice of IRS configuration and scheduling scheme significantly influences overall system performance, offering flexibility for diverse applications.