Opportunistic scheduling for streaming users in high-speed downlink packet access (HSDPA)
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
High-speed downlink packet access (HSDPA) achieves high data rates and high spectral efficiency by using adaptive modulation and coding (AMC) schemes and employing multi-code operation of CDMA. In this paper we present opportunistic algorithms for scheduling HSDPA users and selecting modulation and coding schemes that exploit channel variations to increase the probability of an uninterrupted media play-out. First we introduce a discrete event model for HSDPA system to transform the scheduling problem for providing an uninterrupted play-out to a feasibility problem that considers short term and long term quality of service (QoS) constraints. A methodology for obtaining a feasible solution is then proposed by starting with a so called stable algorithm that satisfies the long term QoS constraints (if possible with any scheduling policy). Next, we present stochastic approximation algorithms that adapt the parameters of the stable algorithm in a way that a feasible point for the short term QoS is reached within the feasibility region of the long term QoS.
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 | 0.001 |
| 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