Interference-aware joint user selection and quantised power control schemes for uplink cognitive multiple-input multiple-output system
Bibliographic record
Abstract
The authors investigate the interference-aware joint secondary user (SU) selection/scheduling and quantised power control (JSUS-QPC) schemes for the uplink communication in the cognitive multiple-input multiple-output (MIMO) system. The main objective of JSUS-QPC is to maximise the sum-rate capacity of the cognitive MIMO uplink communication system under the constraint that the interference to the primary user (PU) is below a specified level. The computational complexity of finding an optimal JSUS-QPC scheme by exhaustive search grows exponentially with the number of users and power levels. The authors also show that the JSUS-QPC is a non-deterministic polynomial-time hard problem and present two low-complexity algorithms for JSUS-QPC problem. Also, the effect of different system parameters (e.g. interference threshold level, the number of PUs, the number of SUs, the number of quantised power levels, etc.) on the performance of the proposed algorithms is examined. The proposed algorithms have low computational complexity, and their effectiveness is verified through simulation results.
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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 | 0.003 |
| 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".