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Summary
This summary is machine-generated.

This study investigates user equipment localization using reconfigurable intelligent surfaces (RIS). Findings show that realistic amplitude models, unlike unity assumptions, improve accuracy but impact data rates in near-field scenarios.

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Area of Science:

  • Wireless communication
  • Signal processing
  • Electromagnetics

Background:

  • Accurate localization of user equipment (UE) is crucial for advanced wireless services.
  • Reconfigurable intelligent surfaces (RIS) offer potential for enhancing wireless communication environments.
  • Existing models often oversimplify RIS behavior, particularly amplitude variations.

Purpose of the Study:

  • To analyze user equipment localization performance using RIS-based lenses in the uplink.
  • To evaluate the impact of realistic RIS phase-dependent amplitude variations on localization accuracy and data rates.
  • To propose a simplified localization algorithm to mitigate computational complexity.

Main Methods:

  • Fisher Information Matrix (FIM) analysis for localization performance.
  • Modeling of actual RIS phase-dependent amplitude variations.
  • Development of an angular expansion-based localization algorithm.
  • Near-field region analysis of Position Error Bound (PEB) and Root Mean Square Error (RMSE).

Main Results:

  • Superior localization performance is achieved with prior location information.
  • Realistic RIS amplitude models reveal increased localization error and degraded data rates for amplitude values less than one in the near-field.
  • The widely used unity amplitude assumption for RIS phase shifts is demonstrated to be inaccurate.

Conclusions:

  • Realistic modeling of RIS amplitude variations is essential for accurate near-field localization.
  • The proposed angular expansion algorithm offers a computationally efficient approach to localization.
  • Future research should consider these realistic amplitude effects for optimized RIS-aided wireless systems.