Joint antenna selection and grouping in Massive MIMO systems
Bibliographic record
Abstract
Massive MIMO (Multi-Input Multi-Output) is considered as a promising technology for the fifth generation of wireless communication systems (5G). In this paper, we deal with the CSI feedback reduction issue when a base station (BS) equipped with a large number of antennas serves a limited number of receiver nodes disposed in several groups. This paper considers the practical case where spatial correlation exists among the transmit antennas of the BS. We propose a novel scheme that achieves a considerable reduction in CSI feedback overhead communicated by the receiver nodes to the BS. The proposed approach performs a joint antenna selection and grouping to handle the spatial correlation issue. To this end, we propose a low complexity algorithm that runs antenna selection distributively at each group of receiver nodes. We show that the proposed scheme offers enormous reduction in CSI feedback while ensuring acceptable performance in terms of achievable sum-rate and low computational complexity thanks to its greedy nature.
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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".