Optimized Carrier Sensing Thresholds for Dense mmWave Wireless Networks Coexistence
Bibliographic record
Abstract
Densification is an essential paradigm for future wireless networks in the unlicensed millimeter-wave (mmWave) band. Despite the promises of multi-gigabit data rates in mmWave due to wide spectrum availability, high node density could lead to severe interference and channel contention that reduce spatial reuse and overall throughput performance. To that effect, this paper investigates an approach to improve spatial average of throughput by optimizing the carrier sensing thresholds that govern the effectiveness of the channel access protocols. We consider a network with two radio access technologies (RATs) coexisting in the unlicensed mmWave spectrum. Using stochastic geometry tools to model network density, channel access protocols and spatial statistical average of throughput, closed-form expressions are proposed for selecting the carrier sensing thresholds without requiring frequent channel sounding to obtain network information. Numerical results obtained through simulation demonstrate the effectiveness of optimizing the carrier sensing thresholds to account for node density, transmit power and the mmWave propagation characteristics.
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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 | 0.000 | 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 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".