Metasurfaces: physics and applications in wireless communications
Bibliographic record
Abstract
The ever increasing number of wireless devices and systems has led to a crowded spectrum and increased the demand for versatile and multi-functional wireless apparatuses. Recently, metasurfaces have been explored as a prominent technological solution to the current paradigm of spectrum scarcity by opportunistically sharing the spectrum with various users. In general, metasurfaces are passive/dynamic, ultra-compact, multi-functional and programmable structures that are capable of both reciprocal and nonreciprocal signal-wave transmissions. The controllability and programmability of such metasurfaces are governed through DC bias and occasionally a radio-frequency modulation applied to the active components of the unit cells of the metasurface, e.g. diodes and transistors. This article overviews some of the recently proposed passive and dynamic metasurfaces and shows that metasurfaces can enhance the performance of wireless communication systems thanks to their unique physical features such as real-time signal coding, nonreciprocal-beam radiation, nonreciprocal beamsteering amplification and advanced pattern-coding multiple access communication.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".