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Performance Analysis and Design Principles of Wireless Mutual Broadcast Using Heterogeneous Transmit Power for

Taesoo Kwon1, HyeonWoo Lee2

  • 1Department of Computer Science and Engineering, Seoul National University of Science and Technology (SeoulTech), Seoul 01811, Republic of Korea.

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Summary
This summary is machine-generated.

This study models heterogeneous random access-based wireless mutual broadcast (RA-WMB) performance with varying transmit power. It introduces an equivalent transmit power for comparison and an optimization method for better network management in beyond 5G/6G systems.

Keywords:
6G IoTheterogeneous devicesneighbor discoverypower controlproximity-based servicesrandom accessstochastic geometrywireless broadcast

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Area of Science:

  • Wireless communication networks
  • Beyond 5G and 6G systems
  • Network performance analysis

Background:

  • Proximity-aware services are crucial for future 5G/6G applications.
  • Managing heterogeneous devices (sensors, IoT) with diverse capabilities is essential.
  • Random Access-based Wireless Mutual Broadcast (RA-WMB) is a key technology.

Purpose of the Study:

  • To analytically model and characterize the performance of RA-WMB in heterogeneous environments with distinct transmit (Tx) power levels.
  • To enable quantitative comparisons between heterogeneous and common Tx power configurations.
  • To optimize Tx power allocation for balanced network performance.

Main Methods:

  • Utilized a marked Poisson point process to model nodes with various Tx power levels.
  • Derived an equivalent Tx power to represent heterogeneous performance relative to a common Tx power.
  • Formulated an optimization problem for Tx power configuration and proposed a closed-form suboptimal transmission probability (TxPr).

Main Results:

  • Developed an analytical framework to represent heterogeneous RA-WMB performance using an equivalent common Tx power.
  • Derived performance ratios among different node groups based on their Tx power.
  • Identified an optimal Tx power configuration and an efficient suboptimal TxPr for performance enhancement.

Conclusions:

  • The proposed analytical model accurately represents heterogeneous RA-WMB performance.
  • The optimization strategy effectively balances individual and overall network performance.
  • The findings provide valuable insights for designing efficient RA-WMB in future wireless networks.