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Unit Cell Design in Reconfigurable Intelligent Surface Array in Beam-Steering Applications

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A Reconfigurable Intelligent Surface (RIS) is a programmable surface structure used to control the electric and magnetic properties of reflected signals. It controls the reflected signal characteristics, such as polarization and phase, dynamically. The strategic placement of RIS in the wireless channel between transmitter and receiver enhances the link quality by steering the reflected signals towards the receiver. RIS can be implemented either using antenna arrays or metasurfaces. In this paper, an antenna arrays based RIS design approach is followed, and a reconfigurable 'unit cell' is designed using rectangular microstrip patch antennas at 26 GHz frequency for beam-steering applications. Unit cells with 6.7 mm × 7.5 mm dimensions, coupled with variable slot lengths, yield a comprehensive range of phase variations. PIN diodes were selected as the reconfiguration elements due to their rapid switching capabilities and relatively low insertion loss at the target frequency of 26 GHz. A careful alteration of unit cell geometry and strategic placement of tuning elements on the resonating patch are proposed. Its behaviour is examined when reconfigurable unit cells are arranged as an array structure.

Original languageEnglish
Title of host publicationProceedings of 3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1522-1526
Number of pages5
ISBN (Electronic)9798331574574
DOIs
Publication statusPublished - 2026
Event3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026 - Bangkok, Thailand
Duration: 11-03-202613-03-2026

Publication series

NameProceedings of 3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026

Conference

Conference3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026
Country/TerritoryThailand
CityBangkok
Period11-03-2613-03-26

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Optimization
  • Health Informatics
  • Computer Science Applications
  • Information Systems and Management

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