Beamforming Techniques for NOMA-Based Integrated Sensing and Communication Systems
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Bibliographic record
Abstract
In this paper, beamforming techniques are proposed for an integrated sensing and communication (ISAC) system based on non-orthogonal multiple access (NOMA). Specifically, a multi-antenna dual-functional base station simultaneously performs target sensing and serves multiple single-antenna NOMA communication users. To investigate the potential capabilities of this NOMA-based ISAC system, we first develop a beamforming technique for the max-min signal-to-interference-and-noise ratio (SINR) balancing problem. However, the original form is not convex regarding the design parameters. We propose an iterative algorithm that uses a bisection search to address the non-convexity problem and achieve a feasible solution to the original SINR balancing problem. This approach involves solving an equivalent power minimization problem, where we exploit the semidefinite relaxation technique. We also consider a robust design for the power minimization problem by taking into account inevitable imperfect channel state information. The numerical results show that the proposed NOMA-based ISAC performs better than the conventional orthogonal multiple access-based ISAC system in terms of transmit power consumption and balanced SINR while meeting the quality of service requirements regardless of the uncertainty of the associated channel.
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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 | 0.001 | 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 it