High performance homodyne six port receiver using memory polynomial calibration
Bibliographic record
Abstract
This paper proposes an optimized memory polynomial (MP) based calibration technique for a homodyne six-port receiver. The performance and complexity of the proposed calibration technique allows for an easy implementation and high linearity performance of the homodyne receiver. For validation purpose, a six-port receiver was implemented and tested using a 3G (WCDMA) signal in the case of a multipath fading channel. The MP calibration technique was implemented and tested. By sending a training I/Q data into the receiver, the calibration constants were estimated from the diode output voltages using the least square algorithm. Subsequent analysis using a 3D plot of the error vector magnitude (EVM), non-linearity order (N) and memory depth (M) of the MP was done to optimize the complexity in terms of the number of calibration constants to ensure a good receiver performance. A bit error rate profile of the communication system was finally plotted to show the viability of the SPR front-end in a high data rate communication system even in the presence of a multipath fading channel.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".