Accurate Power Efficiency Estimation of GHz Wireless Delta-Sigma Transmitters for Different Classes of Switching Mode Power Amplifiers
Bibliographic record
Abstract
This paper proposes a new closed-form expression for computing the power efficiency of delta-sigma (DS) radio frequency (RF) transmitters. Due to the large bandwidth of the pulsewidth modulated (PWM) signal at the output of the DS modulator, the peak efficiency of the power amplifier (PA) when driven by a PWM signal is considerably different than its peak efficiency when the input signal is a continuous sine wave. A weight averaging of the efficiency over the frequency bandwidth of the PWM signal is considered for accurate estimation and prediction of the power efficiency of DS RF transmitters. It is shown that, for a low-pass DS transmitter, the overall average power efficiency of the DS transmitter can be accurately estimated by the product of the modulated peak efficiency of the PA and the coding efficiency of the modulator. For bandpass DS transmitters, an additional parameter that accounts for the duty cycle effect on the efficiency of switching-mode PAs has to be considered. To validate the new proposed expression, a DS transmitter for WiMAX, CDMA and EDGE standards is designed, prototyped and tested. The comparison of the simulated and measured efficiencies of the DS transmitter proves the validity and accuracy of the proposed expression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".