Adaptive Transceiver Architecture With QoS Provision for OCDMA Network Based on Logic Gates
Bibliographic record
Abstract
Utilization of an adaptable transceiver with quality of service (QoS) features is a promising notion to build next generation optical network. This paper proposes an adaptive transceiver design by adopting logic gates in the optical domain. The proposed design offers multiple scenarios to support QoS diversity with a slight modification of conventional optical code division multiple access (OCDMA) transceiver architecture through Sigma Shift Matrix (SSM) signature code. In particular, the proposed transceiver design categorizes the users into two classes of service, one having a higher quality level and the other having a lower quality level. Users of high class transmit at low interference versus high interference power for low classes’ users. To switch between the multiple scenarios, an optical Mux performs digital operation is developed and integrated to the transceiver design. This type of MUX is built by using a semiconductor optical amplifier (SOA). In addition, a comprehensive algorithm is developed to control the function of the adaptable transceiver. Five scenarios were formed and investigated to offer a platform for a different type of applications. A proof concept using Optisystem software demonstrates ability of the proposed architecture to efficiently switch between different levels of QoS as per user requirement and provide desired transmission capacity.
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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 | 0.000 | 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 | 0.000 | 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".