DSP techniques for linearity and efficiency enhancement of multi-band envelope tracking transmitters
Bibliographic record
Abstract
Due to the increasing demands for large capacity and high performance wireless transmitters, multi-band transmitter architectures play an important role in modern communications. Thus, advances in the design techniques of radio frequency (RF) power amplifiers (PAs) have promoted the use of a single multi-band PA and RF components in order to concurrently process multiple input signals located in different frequency bands. In this paper, digital signal processing (DSP) techniques for linearity and efficiency enhancement of multi-band envelope tracking (ET) transmitters are discussed. A two-dimensional digital predistortion (2D-DPD) is used for linearization of the dual-band PA around each band separately, relaxing the high speed requirements needed by wideband DPD. Power efficiency enhancement of the dual band PA is accomplished by adopting bandwidth reduced envelope shaping functions that depend on the original envelopes of the two concurrent signals driving the PA, which provides a good compromise between efficiency and linearity. The proposed architecture is experimentally validated where linearization and efficiency enhancement results are presented.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".