An SMDP-Based initial radio access technology selection method for heterogeneous wireless networks
Bibliographic record
Abstract
Heterogeneous Wireless Networks (HetNets) are a class of networks that have been designed to provide an open and flexible architecture for the coexistence of various distinct Radio Access Technologies (RATs). In such networks, one of the key challenges is the selection of the best available RATs when a user is connected upon making an incoming service request. This thesis proposes a Joint Call Admission Control (JCAC) - based approach for initial RAT selection in HetNets composed of two co-located wireless networks . The RAT selection problem in such HetNet is formulated by using a JCAC-based Semi-Markov Decision Process (SMDP) model, where the JCAC policy is determined according to a network cost function that weights three parameters: a cost of blocking the incoming service request, a cost of accessing RAT, and the RAT energy consumption cost. Simulation results are provided, showing the benefits of our approach in terms of RAT selection and resulting network energy consumption cost .
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".