Randomly tiled rectangular sub-arrays for side lobe and grating lobe reduction in mm-Wave limited scanning phased array
Bibliographic record
Abstract
In 5G communication system a high gain steerable phased array is desired. In this paper, a novel mm-Wave 256 element phased array system based on 8 element sub-arrays is presented. The sub-arrays are randomly tiled so the periodicity in the array is disrupted and significantly reduce the side lobe level (SLL). Four different rectangular sub-arrays: 1×8, 8×1, 2×4 and 4×2 are used to completely fill the phased array aperture. The steering range is ±15° in both Azimuth and Elevation planes achieving <; -10dBc grating lobe/SLL and better than 60% aperture efficiency. This technique greatly reduces the required array control circuits in a large-scale array. It can be a great candidate for multi-Giga-bit/s (Gbps) 5G communications and it can be realized with multilayer technologies such as low temperature co-fired ceramic (LTCC).
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 | 0.000 |
| 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 | 0.000 |
| 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".