Uplink scheduling for supporting real time voice traffic in IEEE 802.16 networks
Bibliographic record
Abstract
This paper studies real-time traffic support in IEEE 802.16-based backhaul networks, where each subscriber station (SS) may be responsible for forwarding packets for a number of real-time voice connections. In an 802.16-based network, the SS requests bandwidth to the base station (BS) in the uplink, and bandwidth grants are sent back from the BS through the downlink. The 802.16 standard specifies that the bandwidth requests are for individual connections and pass only the number of bytes requested from each connection. The standard does not specify a resource allocation strategy. In this paper we propose a simple enhancement to the bandwidth request mechanism in 802.16 for supporting packet voice traffic. First, the SS combines the bandwidth requests of multiple connections associated to it and sends aggregate bandwidth requests to the BS. This makes the bandwidth request process more efficient by saving transmission time of both the BS and the SSs. Second, in order to facilitate the BS to make resource allocation decisions, the aggregate bandwidth requests include information about the latency requirements of buffered real-time packets at the SSs. We propose three different bandwidth request and packet scheduling schemes, each of which requires a different amount of information to be included in the bandwidth requests. Our results show that there is an optimum point about how much delay information the SS should report to the BS in order to best utilize the uplink resources while providing satisfactory real-time performance for the voice traffic.
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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 | 0.001 | 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".