Characterization of Multipath Persistence in Device-to-Device Scenarios at 30 GHz
Bibliographic record
Abstract
Due to high blockage loss of millimeter wave (mmwave) channel, researchers proposed to use multipath components (MPCs) as alternative communication links when line of sight (LOS) signal gets blocked. However, when both link ends are moving such as in Device-to-Device (D2D) scenario, MPC parameters show variation in their characteristics. In such scenarios, MPCs need to be persistent with transmitter/ receiver's movement in order to be used as a communication link. The main goal of this paper is to the characterize persistent MPCs for the mm-wave propagation channel at 30 GHz frequency in an urban environment. To this end, we develop a set of algorithms to resolve these MPCs. We investigate how persistent MPCs evolve and changes their characteristics in both temporal and angular domain with receiver's movement. We also analyze the probability of occurrence of persistent paths of different lengths and differential change of their azimuth angle of arrivals (azimuth- AOAs) throughout the movement. These information of persistent paths will help the system developer to design blockage effect immune communication links for D2D user.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".