Multiport Transmitter Front-End Architecture for Concurrent Dual-Band Digital Predistortion
Bibliographic record
Abstract
This brief proposes a multiport transmitter front-end (MTFE) architecture to bolster the concurrent dual-band transmission while supporting the digital predistortion (DPD) processing. The proposed architecture consists of two back-to-back multiport networks driven by only one local oscillator (LO) through a multilayer power divider. The low-power LO source can effectively suppress the growth of intermodulations in/between the transmit and DPD feedback loop, thereby optimizing transmission performance. Furthermore, the architecture makes full use of the mainstream DPD architectures, like the frequency-selective (FS) method, to migrate the in-band/cross-band distortions and the adjacent channel interference (ACI) caused by the nonlinearity of the power amplifiers. In experiments, we evaluate the performance of the proposed MTFE architecture over the QAM and OFDM signals. The results consistently demonstrate excellent DPD performance under concurrent dual-band transmission.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".