Polarization division multiple access with polarization modulation for LOS wireless communications
Bibliographic record
Abstract
Abstract In this paper, we discuss a potential multiple access and modulation scheme based on polarized states (PS) of electromagnetic (EM) waves for line-of-sight (LOS) communications. The proposed scheme is theoretic different from the existing polar modulation for EDGE and WCDMA systems. We propose the detailed bit representation (modulation) and multiple access scheme using PS. Because of the inflexibility of polarization information in the time and frequency domains, as well as independence of frequency and space, the polarization information can be used independently for wireless communications, i.e., another independent resource domain that can be utilized. Due to the independence between the PS and the specific features of signals (such as waveform, bandwidth and data rate), the discussed polarization division multiple access (PDMA) and polarization modulation (PM) are expected to improve the spectrum utilization effectively. It is proved that the polarization filtering technique can be adopted in the PDMA-PM wireless communications to separate the multiuser signals and demodulate the bit information representing by PS for desired user. Some theoretical analysis is done to demonstrate the feasibility of the proposed scheme, and the simulation results are made to evaluate the performance of the suggested system.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".