QoS- based JPEG images transmission protocol for wireless CDMA communication systems
Bibliographic record
Abstract
In recent years, wireless communication systems have become increasingly popular as an inexpensive and promising means for ubiquitous and wireless multimedia communications. However, before wireless multimedia appliances become a common commodity several challenging issues need to be resolved. Wireless communication channels are characterized by long bursts of data errors, and ambient noise, propagation losses, multipath, interference, and properties arising from the use of multiple antennas pose a serious problem to information transmission over wireless networks. In this paper, we propose a QoS-based modified scheme to transmit JPEG-coded images over wireless channels for CDMA communication systems, based upon a combination of a modified MAP (Maximum Aposteriori Probability) decoding to eliminate error transmissions and a fast decorrelating multiuser detection mechanism as a post-processing task to eliminate the MAI (Multiple Access Interference) interference. We describe our transmission protocol, and report on its performance evaluation using a simulation testbed we have designed for this purpose. Our results clearly indicate that our protocol improves significantly the quality of transmitted JPEG images over wireless CDMA systems and the transmission errors are significantly reduced when compared to regular transmissions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".