A Performance Evaluation of Millimeter-Wave Cellular Networks with User Mobility
Bibliographic record
Abstract
Millimeter-Wave (mmWave) communications may be the key technology for the realization of 5G networks. MmWave communications have significantly different propagation characteristics than microwave (μWave) frequencies. The recent studies have determined the performance of cellular mmWave networks using stochastic geometry technique assuming a stationary user. The stationary user model does not capture correlation in the blocking of the links as the user moves on. In this work, we have determined the performance seen by a mobile user traveling over a path at constant and varying speeds. We have obtained the cumulative information received by the user as a function of its path length for different blocking intensities and cell sizes. The results show that while the received information rate does not vary significantly with mobility, the average path length that the mobile user is associated with a base station without interruption drops down sharply with increasing blocking intensity. This will cause in high handover rate, which will result in high overhead. This work demonstrates the significance of the user mobility on the performance of cellular mmWave 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".