Bibliographic record
Abstract
Massive machine type communication (MTC) is one of the use cases for IMT-2020. Concurrent accesses of a cellular network by mass MTC devices may result in intolerable delays, packet loss, or even service unavailability to human-tohuman (H2H) communication services. Hence, proper overload control mechanisms are required to guarantee network availability and quality of H2H services under heavy MTC load. In this lecture, we introduce the current 3GPP Long Term Evolution Advanced (LTE-A) random access procedure and the radio access network overload control solutions within LTE/LTE-A. An overview of the several considered overload control solutions, including the standardized Extended Access Barring (EAB) solution, will be briefly introduced. We present an iterative contending-user estimation (ICE) method for the analysis of multi-channel slotted ALOHA protocol in transient conditions and with non-stationary arrivals. We then demonstrate how to use the ICE method to model LTE-A random access procedure and estimate the RACH performance under different overload control schemes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".