Inflight Broadband Connectivity Using Cellular Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After three decades from the public debut of cellular networks, there are hardly parts of populated lands where cellular coverage is absent. Day after day, mobile users have been provided with wider range of services at higher speed. Today, long terminal evolution (LTE) networks support broadband connectivity for users moving as fast as 350km/h, and the support for speeds up to 500km/h is under consideration. Unfortunately, none of these efforts were aimed at airborne travelers due to the lack of aerial coverage. Provided that 5G networks are meant to provide anywhere and anytime connectivity for anyone, many operators are providing the free onboard Wi-Fi through proprietary terrestrial networks or satellite links. Unfortunately, both of these solutions have serious drawbacks, where the latter provides very limited speed, and the former is expensive and unscalable. In this paper, we discuss the technical possibilities of enhancing the existing LTE infrastructure for air to ground communications. We identify the major challenges and obstacles in this path, such as uplink/downlink interferences, frequent roaming, large Doppler effect, and channel degradation. We also discuss appropriate solutions to counteract them using some of the emerging antenna, signal processing, beamforming, and multi-beaming ideas.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it