An Efficient Video Adaptation Scheme for SVC Transport over LTE Networks
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Bibliographic record
Abstract
Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) offers high data rate capabilities to mobile users, and, 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 enabling this. In this paper, we are proposing an efficient adaptation scheme for Scalable Video Coding (SVC) transport over LTE networks and investigate the benefits of this scheme for video streaming over LTE networks. Video streaming over LTE networks is analyzed using a 3GPP compliant LTE simulator using H.264 and SVC video traces. Analysis is done using real time use cases of mobile video streaming. Different parameters like throughput, packet loss ratio, delay, and jitter are compared with H.264 single layer video for unicast and multicast scenarios using different kinds of scalabilities. Results show that considerable packet loss reduction and throughput savings (18 to 30%) with acceptable video quality are achieved with proposed scheme based on SVC compared to H.264. Advantages of proposed scheme for LTE networks are evident from the simulation results.
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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 | 0.000 | 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 | 0.001 | 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