RIS-Assisted Spatial Modulation and Space Shift Keying for Ambient Backscattering Communications
Bibliographic record
Abstract
In wireless communications, reconfigurable intelligent surfaces (RIS) are emerging as a promising technology that is made possible by the advent of software controlled metamaterial sheets for controlling the wireless channels dynamically. In future applications, IoT devices will have small sizes and limited power supply. To make these devices spectrally and energy efficient in accordance with the advanced 5G and 6G specifications, we propose ambient backscattering (ABSc) technique along with spatial modulation (SM) and space shift keying (SSK) for data transfer assisted with RIS. We also conduct a thorough performance analysis of these schemes in terms of outage probability, and bit error rate, validated by Monte-Carlo simulations, and provide comparative results that illustrate the merits of the proposed techniques. In particular, it is shown that RIS-empowered SM and SSK along with ABSc perform much better than conventional communications.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".