Advanced envelope delta-sigma transmitter architecture with PLM power amplifier for multi-standard applications
Bibliographic record
Abstract
This paper presents a new modified envelope delta-sigma (DS) based transmitter architecture with good linearity and efficiency performance without applying any linearization techniques. For the proposed transmitter setup, a pulsed load modulation (PLM) amplifier is implemented and used for its high power efficiency at the back-off power levels. For high efficiency performance of the PA and maintaining the linearity of the system, an envelope DS modulator is utilized to quantized standard signals prior to the PA. Simulation results also show that higher coding efficiency of the quantized signal is achievable employing the envelope DS modulator instead of its Cartesian DS modulator counterpart. To validate the proposed technique, a transmitter prototype is implemented and tested with standard signals with various pick-to-average power ratios (PAPRs). Using this transmitter setup for a 3MHz bandwidth LTE signal with 7dB PAPR and a WiMAX signal with 1.25MHz bandwidth and 7.9dB PAPR, the average drain efficiency of about 45% and 44% are obtained, respectively, at the average output powers of 24.8dBm and 25.7dBm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 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".