Detection of M-ary OFDM systems with CPM mapper over multipath channels
Bibliographic record
Abstract
In this paper, a class of OFDM systems with Continuous Phase Modulation (CPM) mapper signals is discussed and theoretical predictions for symbol error probabilities are derived, where the memory is employed to improve system performance. Previously, results summarized that binary data of OFDM systems with CPM mapper is mapped with complex symbols using the concept of correlated phase states of CPM signal. The results presented in this paper show that M-ary OFDM systems with CPM mapper outperforms the conventionally used M-ary memory-less mapper in OFDM systems. Optimum and suboptimum multiple-symbol observation OFDM systems with CPM mapper receivers are derived. Multipath channel with Additive White Gaussian Noise (AWGN) is assumed. Also, symbol error rate performance in terms of high and low SNR bounds is analyzed and assessed in terms of the value of the deviation ratio h, time delay, and attenuation level. This paper provides a complete analysis of the performance of the OFDM systems with CPM mapper at high SNR as well as low SNR and as a result unifies and extends the previously available results.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".