Three-Dimensional Beamforming: A new enabling technology for 5G wireless networks
Bibliographic record
Abstract
It is anticipated that the mobile data traffic will grow 1,000 times higher from 2010 to 2020 with a rate of roughly a factor of two per year. This increasing demand for data in next-generation mobile broadband networks will lead to many challenges for system engineers and service providers. To address these issues and meet the stringent demands in coming years, innovative and practical solutions should be identified that are able to provide higher spectral efficiency, better performance, and broader coverage. Next generations of wireless cellular networks, which are known as fifth generation (5G) or beyond fourth generation (B4G) wireless networks, are expected to produce higher data rates for mobile subscribers in the order of tens of gigabits per second (Gbit/s) and support a wide range of services. Despite the absence of official standards for the 5G, the data rate of 1 Gbit/s per user anywhere for 5G mobile networks is expected to be deployed beyond 2020.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".