Cohen–Merhav bounds on the symbol error rate of uncoded signalling in AWGN interference
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Using a recent Bonferroni‐type inequality proposed by Cohen and Merhav, we develop new tight lower bounds on the word error probability of uncoded systems with optimal Maximum A Posteriori (MAP) coherent detection for non‐uniform signalling over additive white Gaussian noise channel. Our results are compared to the state‐of‐the‐art Kuai‐Alajaji‐Takahara (KAT) lower bounds and it is shown that the superiority of one bound to another is dependent on the signal constellation, the amount of non‐uniformity of the Bernoulli source to be communicated and the SNR range of interest. It is noted that bounding techniques for the performance evaluation of communication systems are receiving increasing attention today, thanks to their suitability for a wide variety of schemes ranging from uncoded signalling to space–time‐coded multiple‐input multiple‐output (MIMO) systems. Copyright © 2007 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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