A Measurement-Based Study of WLAN to Cellular Handover
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
Real-time vertical handover is an important capability for multimode WLAN/cellular handsets. In many cases however, seamless handover can be very difficult to achieve, since WLAN coverage may be lost long before a cellular call leg can be triggered and established. Worse-case handovers of this kind occur when mobile users walk from indoor building WLAN coverage to outdoors during voice connections. In this paper we report on a measurement-based study of WLAN-to-cellular handover. Our results are based on extensive IEEE 802.11 measurements that were made on the McMaster University campus during the summer of 2005. Our methodology involved traversing many indoor-to-outdoor paths for a large number of campus buildings and exits while monitoring multi-AP Wi-Fi coverage. The collected data was then processed to determine the probability of seamless handover using classical vertical handover algorithms. The results presented give important insights into the difficulty of this problem, and relate to issues such as Wi-Fi deployment type, handover triggering, and Wi-Fi link loss threshold. The results provided enable handset designers and WLAN administrators to better understand the sensitivity of vertical handover performance to these parameters and how they can be optimized
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 | 0.000 |
| 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