Rotating cluster mechanism for coordinated heterogeneous MIMO cellular networks
Bibliographic record
Abstract
To increase the average achievable rates per user for cluster-edge users, a rotating clustering scheme for the downlink of a coordinated multicell multiuser multiple-input multiple-output system is proposed in this paper and analyzed in two network layouts. In the multicell heterogeneous cellular network, base stations of a cluster cooperate to transmit data signals to the users within the cluster; rotating cluster patterns enable all users to be nearer the cluster center in at least one of the patterns. Considering cellular layouts with three or six macrocells per site, different rotating patterns of clusters are proposed and the system performance with the proposed sets of clustering patterns is investigated using a simulated annealing algorithm for user scheduling and successive zero-forcing dirty paper coding as the precoding method. The rotating clustering scheme is less complex than fully dynamic clustering, and it is primarily designed to improve the throughput of cluster-edge users. As an extra secondary benefit, it is also capable of slightly improving the average achievable sum rate of the network overall. The effectiveness of the proposed methods with two different scheduling metrics, namely throughput maximization and proportionally fair scheduling, is of interest in this work. Moreover, the speed of rotation affects the performance of the system; the higher the speed of rotation, the more frequently any specific users will be nearer the cluster center. Our simulations demonstrate the effectiveness of the proposed rotational approach and determine the speed of rotation beyond which any additional performance gains become negligible.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".