Integrated Sensing and Communication: NOMA vs Cooperative NOMA
Bibliographic record
Abstract
This paper examines the integrated sensing and communication technology (ISAC) in the downlink scenario where a base station exploits cooperative non-orthogonal multiple access (CNOMA) to jointly offer communication functions to users and sensing functions to targets. CNOMA allows the user with good channel conditions to assist another user with a weak channel using the decode and forward strategy in full duplex mode while forming a beam-pattern that is capable of sensing the targets. The main objective in this work is to maximize the sum rate of the users by jointly optimizing the communication beamformers and the power allocation of the near user subject to the quality of service requirements for sensing and communication functions. The formulated problem is non-convex and hard to solve using traditional solvers. For that reason, a penalty-based approach is adopted to provide an efficient solution. Numerical results demonstrated the advantage of C-NOMA in ISAC, showing gains reaching up to 38% compared to the traditional NOMA, and 65% compared to the spatial division multiple access (SDMA).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".