Delay-Based Admission Control Using Fuzzy Logic for OFDMA Broadband Wireless Networks
Bibliographic record
Abstract
In this paper, we present a fuzzy logic-based admission control algorithm for orthogonal frequency division multiple access (OFDMA)-based broadband wireless networks. The system under consideration is compatible with the IEEE 802.16 standard in the TDD-OFDMA mode of operation. The proposed admission control algorithm considers various traffic source parameters (i.e., normal rate, peak rate and probability of peak rate) and packet-level delay requirements for the traffic to decide whether an incoming connection can be accepted or not. We formulate a queueing model to investigate the impacts of physical layer parameters (e.g., channel quality and number of allocated subchannels) on the radio link layer performances (e. g., average queue length, delay and throughput). The inference rules for resource allocation in the proposed fuzzy logic admission control are defined based on these queueing performance measures. The performance of the proposed admission control algorithm is analyzed by simulations and also compared to those of the traditional schemes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".