Closed-Form Blockage Probability for Relays-Assisted mmWave D2D Communications: Benefits of Using Relays
Bibliographic record
Abstract
One of the important challenges of millimeter wave (mmWave) device-to-device (D2D) communications is its vulnerability to obstacles. While relaying is a possible solution when the direct mmWave D2D link is blocked by obstacles, the selected relay link may also be blocked by dynamic blockers that are difficult to know in advance. This paper focuses on investigating the dynamic blockage effects in relays-assisted mmWave D2D communication systems, where we assume that D2D users can switch to other available relays when the current link is blocked. A closed-form expression for the probability of all available relays being simultaneously blocked for a pair of D2D users is derived, which reveals the effects of the density and position of relays on the blockage characteristics and system reliability. Additionally, a closed-form expression for the minimum relay density required to satisfy certain quality of service requirements is obtained accordingly, and the feasible positions for a relay to effectively reduce the blockage probability is found based on particle swarm optimization. To the best of our knowledge, this is the first work to theoretically analyze the dynamic blockage in relays-assisted mmWave D2D communications, which provides valuable insights for designing network parameters.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".