Performance enhancement of first order three-level envelope delta sigma modulator based transmitter
Bibliographic record
Abstract
This work is concerned with the analysis, based on MATLAB simulation, of 1stand 2ndorder Multi-level envelope delta sigma modulators (EDSMs) that are used for high efficiency and linearity wireless mobile transmitter architectures with an Orthogonal Frequency Division Modulation (OFDM) signal and long term evolution (LTE) signal. The analysis is based on measuring the linearity and the efficiency of the three-level EDSM. It was shown that, at different input signal power levels of the three-level EDSM, 1storder three-level EDSM is able to achieve a performance that is close to the performance of the 2ndorder counterpart. While 1storder DSM requires less circuitry, it is recommended to employ 1storder three-level EDSM instead of using 2ndorder three-level EDSM. 1storder three-level EDSM has a signal to noise distortion ratio (SNDR) and coding efficiency of 58 dB and 77%, respectively. While 2ndorder three-level EDSM showed SNDR of 61.5 dB and coding efficiency of 76.4%. Also, with a long term evolution (LTE) signal, the 1storder EDSM has better performance, in terms of SNDR and CE, than that of the 2ndorder EDSM circuit.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".