Massive MIMO Precoding Methods That Minimize the Variation in Average Power and Active Impedance With Channel Conditions
Bibliographic record
Abstract
This article investigates the impact of precoding on the performance of massive multiple-input multiple-output (mMIMO) transmitters exhibiting nonnegligible antenna crosstalk. For this, a new metric, called the average active impedance, is introduced to quantify the extent of load modulation as a function of the antenna S-parameters and the employed precoding. The new metric is then used to investigate the load modulation under conventional precoding schemes. It is shown that these precoders yield large disparities in average-power levels across the radio frequency (RF) chains, which results in substantial performance variations with channel conditions. Based on this investigation, we propose three new precoding schemes that yield equal average-power (EP) levels across all RF chains, independent of the channel conditions. Numerical simulations and experiments conducted on an mMIMO transmitter prototype confirmed that the proposed schemes improve the transmitter’s resilience to the variation in channel conditions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".