Zero-Padding Space-Time Block Code for Dual-Antenna Backscatter Tag
Bibliographic record
Abstract
Backscatter communications is receiving increasing attention in Internet of Things (IoT), while one major challenge for backscatter communications is that the circuit complexity for high performance tag is also high. In this article, for dual-antenna backscatter tag, we propose a zero-padding space-time block code (ZPSTBC) that can simultaneously improve the tag performance and reduce the complexity of the tag circuit. An interesting thing is that padding zero into space-time block code (STBC) is not beneficial in conventional multi-input-multi-output (MIMO) channels, but may lead to performance improvement in MIMO backscatter channels, from perspectives of error rate and energy harvesting, and also reduce the circuit complexity of the tag. This is due to characteristic of the MIMO structures and tag circuit of backscatter communications. We provide rigorous mathematical analysis and numerical simulations to illustrate the performance improvement and the tag complexity reduction caused by the proposed ZPSTBC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".