Transmit Antenna Selected V-BLAST Systems With Power Allocation
Bibliographic record
Abstract
This paper considers intelligent transmit antenna selection (TAS) combined with power allocation (PA) for closed-loop multiple-input-multiple-output (MIMO) wireless communications. We present two novel TAS techniques for Vertical Bell Laboratories Layered Space-Time (V-BLAST) systems combined with PA that improve the uncoded error rate performance over flat-fading channels. Furthermore, we extend these techniques to V-BLAST with orthogonal frequency division multiplexing (V-BLAST-OFDM) over frequency-selective channels and present TAS techniques combined with space-frequency PA. Computer simulation results demonstrate significant performance gains for these schemes, which can also be achieved with limited rate feedback, even in the presence of channel estimation errors. These techniques seem attractive for cellular reverse link systems, since due to TAS, they can improve performance by using only a small number of transmit radio frequency (RF) chains in the user terminals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".