Performance Analysis of Indoor THz Networks with Intelligent Reflective Surfaces
Bibliographic record
Abstract
The recent breakthroughs in electronic and photonic technologies enabled the design and implementation of intelligent reflective surfaces (IRSs) to manipulate electromagnetic waves and control the wireless environment. A promising application of IRSs is their integration with Terahertz (THz) communications. IRSs can cope with the blockage sensitivity of THz propagation by providing alternative line-of-sight (LoS) links to user equipment (UEs) which are initially blocked. However, deploying more IRSs may degrade the network performance as it leads to non-negligible interference levels. In this paper, we use tools from stochastic geometry to investigate the coverage probability of a downlink (DL) indoor THz network assisted by IRSs, which are added to a subset of the existing blockages. The numerical results reveal that there is an optimal density of IRSs that should be deployed to maximize the coverage of UEs in THz networks.
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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 | 0.003 |
| 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".