UE Position Sensing in Non-LoS Propagation for U6G Wideband XL-MIMO Systems
Bibliographic record
Abstract
In order to enhance the capacity of sixth generation wireless systems, the extremely large-scale multiple-input multiple-output (XL-MIMO) and upper-6 GHz (U6G) propagation are regarded promising technologies. It is imperative to recognize that the unique characteristics of U6G wideband XL-MIMO systems, including hybrid-field and beam squint effects, engender numerous challenges in channel estimation. However, it should be noted that these characteristics can also facilitate user equipment (UE) locating in non-line-of-sight (NLoS) scenarios. Consequently, a multiple-scatterer joint sensing algorithm is proposed. The near-field components are extracted from the hybrid-field channel firstly, and subsequently the spatial parameters are detected in a decoupled manner. The UE position is then effectively located based on the spatial geometry relation between the UE and multiple scatterers. The numerical results demonstrate the efficacy of the proposed UE localization algorithm in NLoS scenarios, while entailing reduced complexity.
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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 | 0.001 | 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".