Downlink Performance and User Scheduling of HetNet with Large-Scale Antenna Arrays
Bibliographic record
Abstract
Considering a heterogeneous network (HetNet) where both macro base station (BS) and small cell (SC) nodes are equipped with large-scale antenna arrays, this paper studies the performance of the BS and SC multiple-input multiple-output (MIMO) downlink systems when the macro and small cells share the same spectrum and hence interfere with each other. Suppose that the large-scale antenna arrays at both macro BS and SC nodes employ maximum-ratio transmission (MRT) precoding and then transmit data streams to their served users simultaneously. Taking into account imperfect channel state information (CSI) obtained by channel estimation, downlink capacity lower bounds for a user in the macro cell and for a user in a small cell are derived as closed-form expressions involving only statistical CSI. Then, two user scheduling algorithms are proposed according to the derived lower bounds. The closed-form expressions for the achievable rates are verified to be accurate predictors for the system performance by Monte-Carlo simulations. Furthermore, numerical results demonstrate the effectiveness of the proposed user scheduling schemes.
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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 | 0.001 |
| Open science | 0.001 | 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".