Dynamic radiation pattern diversity (DRPD) MIMO using CRLH leaky-wave antennas
Bibliographic record
Abstract
This paper presents a dynamic radiation pattern diversity (DRPD) MIMO wireless system where the antennas radiation patterns are electronically controlled in real-time. The adopted antenna elements are composite right/left-handed (CRLH) microstrip leaky-wave (LW) antennas for which the beam direction can be electronically scanned in a continuous manner from backfire to endfire and the beam shape can be controlled. This system offers a tremendous amount of flexibility in tuning the channel transfer matrix to increase the system performance. Based on this architecture, we propose two simple radiation pattern control algorithms. The first one requires no feedback and averages out the channel fades while the second one requires a simple feedback at the receiver to select the beam pattern maximizing the performance metric. The capacity of both algorithms is derived and analyzed using Monte Carlo simulations. The results show that these algorithms significantly improve the wireless link outage performance in a slow fading environment and increase the diversity gain of a MIMO system for a fixed multiplexing gain.
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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".