Efficient Scheduling Algorithms for Multiantenna CDMA Systems
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Bibliographic record
Abstract
In multiple-input-multiple-output (MIMO) multiuser systems, simultaneously serving multiple users achieves high data rates. However, high-performance transmit beamforming requires an adequately designed user-selection scheme. Optimal scheduling can be only obtained through a high computationally complex exhaustive search, and hence, low-complexity heuristic algorithms are required. In addition, employing a multiple-access scheme such as code division (CDMA) largely increases the complexity of optimal scheduling, and it becomes unemployable even for a moderate number of users and antennas. In this context, this paper proposes three heuristic scheduling algorithms for MIMO CDMA systems using zero-forcing beamforming (ZFBF). We use a graph-theoretical approach to model the system as a weighted undirected graph. The problem of user selection is then formulated as a graph coloring problem, namely, the maximum weight <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -colorable subgraph problem. Then, we design two heuristics to solve this graph problem. The first algorithm is a low-complexity greedy algorithm. The second algorithm is based on a tabu search approach to resolve efficiently the complexity/performance tradeoff. Numerical and simulation results show the sub-optimal performances and robustness of the proposed low-complexity algorithms.
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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 | 0.001 |
| 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 it