Bridging the Transition from IEEE 802.11ac to IEEE 802.11ax: Survival of EDCA in a Coexistence Environment
Bibliographic record
Abstract
TGax aims at developing the IEEE 802.11ax protocol to provide enhanced throughput and power efficiency in dense WiFi deployment environments. The new specification shifts the focus from EDCA access to point coordination access, which aims at improving network utilization and power efficiency. Furthermore, it introduces, for the first time, the concept of RU allocation and orthogonal frequency division multiple access (OFDMA) techniques. The new specification addresses the spectral inefficiency in existing transmission by including schedule-based multi-user multiple-input, multiple- output (MU-MIMO) and multi-user OFDMA (MU-OFDMA) techniques to facilitate multi-user uplink transmission for high efficiency (HE) devices. However, complete adoption of the HE protocol is likely to take place over a period of time to offset the deployment cost. To ensure the coexistence of non-HE devices during the transition period, EDCA based single user transmission will remain the basic access technique and a focal point of spectral inefficiency for non-HE devices in the uplink direction. Motivated by our work on the performance of IEE 802.11ac, we propose an EDCA based uplink transmission technique for non-HE devices that allows multi-user transmission to improve spectral efficiency in coexistent WLAN networks.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| 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".