An emerging concept for 4G+ wireless cellular networks: Terminal relaying
Bibliographic record
Abstract
We identify relaying as one of the most effective and enabling components of the LTE-A standard. However, this standard suffers from a major weakness that results from the assumptions that the relaying nodes are static, their locations are known and their number is fixed. While these assumptions facilitate the design of the cellular system, they limit the scope of relay usability. As an alternative, we consider a cellular system in which the wireless terminals (WTs), in addition to transmitting their own signals, act as relays to assist other WTs. In such a system the number of relays scales with the number of WTs offering the system designer significantly more degrees of freedom. However, using WTs as relays presents a number of challenges, including: the mobility of the relaying WTs, the incidental manner in which the relays access the network, the resource blocks (RBs) to which each relay is entitled, the relaying mechanism used by each relay, and the way in which the power is allocated across frequency bands.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".