Downlink Limited Feedback Transmission Schemes for Asymmetric MIMO Channels
Bibliographic record
Abstract
In multiple-input multiple-output (MIMO) broadcast channels, multiuser diversity is exploited by scheduling data transmission to users with best channel conditions. To find the best set of users, the base station requires knowledge of user channels, which for the case of non-reciprocal uplink and downlink channels may lead to a very heavy feedback overhead. In particular, well known transmission schemes for asymmetric MIMO downlink channels with more transmit than per user receive antennas, such as beamforming, require availability of full channel state information (CSI) at the transmitter. In this paper, two multiuser MIMO downlink techniques are presented, which only require partial CSI at the base station. The proposed schemes represent a combination of zero-forcing (ZF) receiver processing with MIMO point-to-point eigenmode transmission and transmit antenna selection. The results show that the scheme which is able to suppress inter-stream interference while maintaining maximum spatial multiplexing and high multiuser diversity gain, achieves higher system throughput.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".