Capacity-Aware Multi-User Massive MIMO for Heterogeneous Cellular Network
Bibliographic record
Abstract
We consider a heterogeneous network (HetNet) where data are delivered from multi-users to a macro-cell base station (MBS) with the help of massive antenna small-cell base stations (SBSs). It is assumed that both the MBS and the small-cell base stations (SBSs) are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. By allowing users with simple omnidirectional antennas to relay their data through a highly directional massive antenna array and focus their transmission in the direction of the MBS, large increases in energy and spectral efficiency can be achieved. Each SBS performs maximum ratio combining (MRC) to detect data from its mobile users and a capacity-aware scheme to beamform the received data to the MBS. The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware HetNet achieves better performance than traditional Eigen-beamforming and requires considerably less computational complexity.
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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 | 0.000 | 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 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".