IEEE Access (Jan 2023)

Practical Evaluation Method of Large Size IRS: Synthesis of Reflection Pattern of Sub-IRS

  • Hiromi Matsuno,
  • Takuya Ohto,
  • Tomofumi Kanno,
  • Takahiro Hayashi

DOI
https://doi.org/10.1109/ACCESS.2023.3313561
Journal volume & issue
Vol. 11
pp. 102072 – 102081

Abstract

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Intelligent reflecting surfaces (IRSs) have been attracting attention as a solution to coverage hole problems in millimeter-wave communication areas and are considered one of the key technologies of next-generation mobile communication systems. To utilize the IRS for mobile networks, the reflection power of the IRS should be evaluated in advance to estimate the coverage enhancement. Because the IRS becomes large, up to several tens or hundreds of wavelengths, a reflection power evaluation method for a large IRS is required. Although the reflection amplitude and phase of the reflecting element are available for the physical optics (PO)-based evaluation method, they depend on the location of the reflecting element because of the mutual coupling between adjacent reflecting elements, and should be measured at each location of the reflecting element. Since the number of reflecting elements in large IRS becomes several tens of thousands, measurement becomes difficult. In addition, although the radar cross section (RCS) is available for reflection power evaluation in the far field, a massive measurement system of several hundreds of meters is required to satisfy the far-field condition of the IRS. For these reasons, the evaluation of large IRS is challenging. To solve this problem, we propose a practical evaluation method for large IRS by synthesizing the RCS patterns of small IRSs (sub-IRSs). Since the influence of the mutual coupling between sub-IRSs depends on the size of the sub-IRSs, we formulated the mutual coupling on the IRS and evaluated the proposed method by changing the size of the sub-IRSs. The measurement results in an anechoic chamber verified that the proposed method can estimate the RCS pattern of a large IRS with a reflection power difference of less than 1dB and the correlation between the estimated RCS pattern and the actual RCS pattern exceeds more than 0.87.

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