Cross layer design for efficient video streaming over LTE using scalable video coding
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
Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) offers high data rate capabilities to mobile users, and network operators are trying to deliver a true mobile broadband experience over LTE networks. Mobile TV and Video on Demand (VoD) are expected to be the main revenue generators in the near future, and efficient video streaming over wireless is the key to achieve this goal. In this paper, we propose a Scalable Video Coding (SVC) based video streaming scheme with dynamic adaptations and a scheduling scheme based on channel quality. Cross layer signaling between Medium Access Control (MAC) and Real Time Transport (RTP) protocols is used to achieve the channel dependent adaptation in video server. Channel Quality Indicator (CQI) feedbacks from User Equipments (UE) are used for dynamic adaptations. An adaptive Guaranteed Bit Rate (GBR) selection scheme based on CQI feedbacks is also presented, and this scheme improves the coverage of the cell. Simulation results indicate improved video quality for more number of users with reduced bit rate video traffic. Approximately 13% video quality gain is observed for users at the cell edge using this adaptation scheme.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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