A reduced complexity channel estimator for linear modulations operating in fading dispersive channels
Bibliographic record
Abstract
A reduced complexity, pilot symbol assisted channel estimator is presented in the paper for linear modulations operating in frequency selective Rayleigh fading channel. Instead of estimating the entire channel impulse response, our estimator only estimates a few derivative fading processes and uses them to construct the channel impulse response estimate. The technique is computationally efficient, especially for applications where the channel delay spread is small. The performance of our estimator, measured indirectly by the bit error of the companion Viterbi receiver, was evaluated for BPSK, with the number of state of the receiver as a parameter. It was found that a 16 state Viterbi receiver provides close to ideal performance. There is no irreducible error floor. To the contrary, a third order diversity effect is observed in a channel with a uniform delay-power profile. When the number of states in the receiver is reduced to 4, only a second order diversity effect is observed. Finally, we note that our receiver is quite robust against fast fading.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".