A state-space model for flat fading channels with a novel method of rational function filter design
Bibliographic record
Abstract
Clarke's model and Jakes' spectrum have been traditionally accepted in wireless channel modeling. In comparison with measured spectra, Jake's spectrum has limitations - it is unbounded and does not incorporate the effect of temporal phase fluctuations. Previous work extended Clarke's model to yield a theoretical power spectrum that is consistent with measured data. The modified spectrum, which includes the effects of phase fluctuations explicitly, is more appropriate as a theoretical basis for channel spectrum analysis and simulations. We develop here a state-space model that represents a wireless channel with these modified spectral characteristics. This is achieved by developing the relationship between a continuous-time state-space model and the theory of the rational transfer function. A novel method for the design of a rational transfer function of a linear system is proposed. The system input is a Gaussian white noise process, which generates a wireless channel with a desired arbitrary power spectrum. We represent the rational transfer function via the observable canonical form (OCF) to obtain the continuous-time state-space model. A discrete-time version of the state-space model is then provided to represent and simulate a discrete-time flat fading wireless channel.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".