Concentric Circular Array Analysis to Overcome Divergence of Vortex Waves for 70 GHz Frequency Link
Bibliographic record
Abstract
Orbital angular momentum (OAM) of waves, also known as vortex, offers a promising way to enhance communication link capacity and diversity. One of the advantages of vortex modal communication is that one can use different signal information within a fixed frequency band. There is no need to expand the frequency bandwidth, change the polarization, or wait for a time to transfer two-way communication. However, there is still work to be done before vortex communication can be considered as a potential for the next wireless network. One major issue when generating and receiving vortex high modes is the limitation of signal power level in comparison with normal waves. In this study we propose using different concentric circular array formations to overcome low power amounts for OAM modes. Through the use of a higher directive vortex mode, it is possible to increase the link budget and deal with the physical phenomena of divergence patterns. Different modes of 0, 1, and 2 are considered when tapering the array elements. The achieved directivity values were 23, 20, and 18 dB for 0, 10, and 16° angles. Helix antenna as the basic element is suggested in theory for a 70 GHz backhaul communication link.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".