Simplified user scheduling and mode selection algorithm for multiuser MIMO systems with limited-feedback CSIT linear precoding
Bibliographic record
Abstract
In this paper we propose a simplified user scheduling algorithm for the downlink of multiuser multiple antenna systems with limited feedback channel state information available at the transmitter (CSIT) and block diagonalization (BD) precoding. In similar work, the perfect CSIT for all users is generally assumed, but it is normally not available. Optimal user scheduling involves exhaustive search, which becomes very complex for realistic numbers of users and transmit antennas. We employ existing vector quantization algorithms to obtain quantized feedback of CSIT. A simplified heuristic user scheduling metric is proposed, which is shown to achieve performance close to that of the exhaustive search method. Further simplification of the greedy scheduling algorithm is obtained with an intermediate user grouping technique. A user-side single antenna/mode selection technique in conjunction with the proposed user scheduling algorithm is also proposed. The proposed algorithm is of low complexity, but provides performance close to a highly complex exhaustive search.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".