Novel Modeling and Calibration Approach for Multiport Receivers Mitigating System Imperfections and Hardware Impairments
Bibliographic record
Abstract
Factors limiting and degrading the performance of a multiport-based receiver system for wideband signals are modeled and a suitable calibration approach is proposed in this paper. The proposed calibration approach uses a new model for linearization of diode power detectors suitable for wideband real (modulated) wireless signals. To verify the proposed model and calibration procedure, a 2-18-GHz wideband six-port-based receiver system is set up and its performance is verified using wireless signals having different bandwidth and modulation schemes. The new calibration algorithm improved the error vector magnitude (EVM) of the receiver system from 7.9% to 1.6% for a 64-QAM signal with a bandwidth of 2 MHz and a data rate of 12 Mb/s. To show the usefulness of the model for real communication signals, wideband code division multiple access (WCDMA) and wireless local area network (WLAN) signals are received and EVM of 4.7% and 3.4% are reported for the WCDMA and the WLAN signals, respectively.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 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".