WLC04-5: Bandwidth Allocation in 4G Heterogeneous Wireless Access Networks: A Noncooperative Game Theoretical Approach
Bibliographic record
Abstract
Fourth generation (4G) wireless networks will provide seamless high bandwidth connectivity with quality-of-service (QoS) support to mobile users where a mobile will be able to connect to several wireless access networks simultaneously. In such a scenario, bandwidth allocation to a mobile from different types of networks will depend on the traffic load characteristics in each access network. In this paper, we formulate the bandwidth allocation problem in a 4G heterogeneous wireless network as an oligopoly market competition. In an oligopoly market, a few firms provide service/product to the customers. Here, we model the firms as the different types of networks offering bandwidth to the connections in order to maximize the system utility. A Cournot game is used to model this market competition and Nash equilibrium is considered to provide a stable solution. We propose two algorithms, namely, iterative and search algorithms, to obtain the solution. Based on the proposed bandwidth allocation algorithm, we present an admission control mechanism to ensure that the QoS of new and ongoing connections are maintained at the target level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".