Characterizing the performance of beamforming WiFi access points
Bibliographic record
Abstract
Recently beamforming WiFi access points (APs) have been commercially available from multiple vendors. The promise of beamforming APs is the enhanced range and data transmission rate, albeit at a premium price for the AP which can be an order of magnitude more expensive than regular omnidirectional APs. In this work, through live measurements, we study the throughput performance of beamforming APs and compare it with that of regular omnidirectional APs. We consider two systems with multiple WiFi clients and: 1) a single expensive beamforming AP, and 2) multiple low-cost omnidirectional APs. We find that while in some situations the beamforming AP outperforms multiple regular APs when downloading data, in other scenarios typical of home and office use, multiple regular APs results in higher throughput and service quality. Moreover, multiple regular APs always outperforms the beamforming AP when uploading data.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".