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Record W7116737468 · doi:10.1109/lawp.2025.3646699

Single-Feed Multifunctional Reflectarray Enabling Quad-Polarization Switching and Wide-Angle Scanning

2025· article· W7116737468 on OpenAlexaff
Guowei Li, Yuehe Ge, Ziheng Zhou, Jiade Yuan, Zhimeng Xu, Zhizhang David Chen

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2025
Typearticle
Language
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsDalhousie University
FundersNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsReconfigurabilityBandwidth (computing)Reconfigurable antennaPolarization (electrochemistry)Phase controlCommunications satelliteWirelessPhase (matter)

Abstract

fetched live from OpenAlex

This letter presents a reconfigurable reflectarray (RRA) capable of generating quad-polarization scanning beams with a fixed linearly polarized (LP) feed. Each element integrates four PIN diodes, providing 1-bit phase control for LP waves and 2-bit control for circular polarization (CP) waves. Using a beam-coding strategy inspired by Pancharatnam–Berry (PB) phase manipulation, the reflectarray can switch among LP, cross-LP, left-hand CP (LHCP), and right-hand CP (RHCP) states. Notably, distinct 1-bit and 2-bit phase compensations are employed for the LP and CP modes, respectively. A 16 × 16 Ku-band prototype was fabricated and experimentally characterized. Measurements demonstrate beam scanning up to ±60°, with peak gains exceeding 21 dBi and 3-dB gain bandwidths of 19.0% in LP mode, 19.5% in cross-LP mode, and 16.9% in both CP modes. Compared with prior works, the proposed design achieves wider bandwidth and quad-polarization reconfigurability with a structurally simpler single-feed configuration, making it attractive for polarization-diverse applications such as satellite communications, airborne platforms, and emerging wireless systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.238
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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