Impact of improper Gaussian signaling on hardware impaired systems
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we accurately model the hardware impairments (HWI) as improper Gaussian signaling (IGS) which can characterize the asymmetric characteristics of different HWI sources. The proposed model encourages us to adopt IGS scheme for transmitted signal that represents a general study compared with the conventional scheme, proper Gaussian signaling (PGS). First, we express the achievable rate of HWI systems when both PGS and IGS schemes are used when the aggregate effect of HWI is modeled as IGS. Moreover, we tune the IGS statistical characteristics to maximize the achievable rate. Then, we analyze the outage probability for both schemes and derive closed form expressions. Finally, we validate the analytic expressions through numerical and simulation results. In addition, we quantify through the numerical results the performance degradation in the absence of ideal transceivers and the gain reaped from adopting IGS scheme compared with PGS scheme.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it