Handoff Rate Analysis in Heterogeneous Wireless Networks with Poisson and Poisson Cluster Patterns
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Bibliographic record
Abstract
In multi-tier heterogeneous wireless networks (HWNs), both horizontal and vertical handoffs impact the signaling overhead and quality of service in the system. However, they are difficult to analyze due to the diverse and irregularly shaped cells in HWNs. The causes of this irregularity are three-fold: (1) small-cell base stations (BSs) tend to be deployed with a high level of spatial randomness; (2) BSs are likely to aggregate around highly populated geographical regions; (3) various transmission power levels in different tiers further create diverse cell sizes and shapes. In this work we present a new stochastic geometric analysis framework on user mobility in HWNs. Each tier of BSs is modeled as either a Poisson point process (PPP) or a Poisson cluster process (PCP), to capture their spatial randomness and their non-uniform and dependent aggregation in space. Flexible user association is also taken into consideration, such that various scales of cell sizes are accommodated. We derive analytical expressions for the rates of all handoff types experienced by an active user with arbitrary movement trajectory. We also demonstrate an example application of the proposed analysis, in optimizing the multi-tier BS selection by users, to balance the tradeoff between data rate and handoff overhead. Finally, extensive simulation is conducted to validate the correctness and usefulness of our analysis.
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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