Design and hardware implementation of Look-Up Table predistortion on ALTERA stratix DSP board
Bibliographic record
Abstract
This paper presents the design procedure and implementation results of a 16 quadrature amplitude modulation (16-QAM) look up table (LUT) predistortion technique for satellite communications using Altera DSP board. The implementation uses Matlab/Simulink, Altera DSP builder and Altera Stratix DSP EP1S80 development board. The design is first implemented in Matlab/Simulink environment. It is then converted to VHDL level using the signal compiler block of the Altera DSP builder. The design is synthesized and fitted with Quartus II software, and downloaded to Altera Stratix DSP EP1S80 development board. The results show that by using LUT pre-distortion, we can get an undistorted constellation at the output of the Traveling Wave Tube (TWT) amplifier. The paper also presents the quantization effects on Symbol Error Rate (SER) performance and SER performance of a 16-QAM modulation with and without using LUT pre-distortion. The results show that the quantization has effect of about 0.3 dB, and the SER performance can be improved significantly (about 5 dB) when LUT pre-distortion is used.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".