An Innovative Architecture for a Non-Ideal Parallel Sub-Sampling Wireless Receiver
Bibliographic record
Abstract
The main bottleneck in broadband reconflgurable (or software-defined) radio systems is the fast analog-to-digital converters (ADC) required to capture the entire system band. Such ADCs are typically costly, consume a lot of power, and have non-ideal transfer characteristics, as well as a limited spurious-free dynamic range (SFDR). This cost problem is compounded in multi-antenna and MIMO (multiple input, multiple output) systems where the entire RF chain, including the ADC, must be replicated for every receiving antenna. This paper presents an architecture where each ADC in a MIMO transceiver is replaced by several slower and less expensive ADCs, effectively partitioning the sampling problem. Furthermore, the combining of the subsampled information streams is done in a dynamically adaptive fashion, in conjonction with the standard space-time processing performed in MIMO systems. Among the many potential advantages of this arrangement, the ability to track and compensate for sample clock jitter is emphasized in this paper.
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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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".