Cooperative Resource Management in Cognitive WiMAX with Femto Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
WiMAX with femto cells is a cost-effective next generation broadband wireless communication system. Cognitive Radio (CR) has recently emerged as a promising technology to improve spectrum utilization by allowing dynamic spectrum access. There will be large potential benefits by applying the CR technique to WiMAX with femto cells, which are barely explored in the literature. In this paper, we propose a novel cognitive WiMAX architecture with femto cells, where the base station and users are equipped with CRs and intelligently adjusts power, channel, and other resources to accommodate the entire network ecosystem. In this new design, we develop an optimization framework for location-aware cooperative resource management, by jointly employing multi-hop cooperative communication, power control, channel assignment, primary user protection, buffer management, and fairness, and incorporating user, channel, and cooperative diversities. To achieve optimality, it is designed based on stochastic Lyapunov optimization, aiming to take advantage of the radio flexibility and fully utilize the spectrum. Evaluated by the rigorous analysis and extensive simulations, our resource management protocol is near-optimal with closed-form bounds, with which cognitive WiMAX achieves substantial performance improvement.
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.
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 it