MIMO space-time correlation model for microcellular environments
Bibliographic record
Abstract
We present a comprehensive cross-correlation model for a multiple-input multiple-output Rayleigh fading channel in an isotropic scattering environment. The scattering environment is assumed to be a microcellular media with sufficient number of scatterers. This implies uniformly distributed angle of departure and angle of arrival either at the transmitter or at the receiver. Simple and reasonable assumptions are made for various relevant physical parameters, such as exponential or normal time-delay distribution and uniform phase change in the receiving waveform. A novel method of modeling is suggested to consider a geometry for the local scatterers. This approach establishes a mathematical relation between the time-delay and the channel gain associated to each dominant propagation path, and uses appropriate probability density function (pdf) for the time-delay profile. This flexible method allows us to characterize a wide range of propagation environments. Cross-correlation function between channels appears to be a multiplication of tow Bessel functions, and two other multiplicative terms. Bessel functions represent the Doppler effect, the carrier frequencies, and the spatial separation, either at the transmitter or at the receiver. The effect of the carrier frequencies also appears on the other terms. Interestingly, the last two terms are /spl eta//2-order derivative of the moment generating function of the delay profile at two carrier frequencies, respectively, where /spl eta/ is the environment pathloss exponent. Overall, the model has a closed form and is a generalization of the Clark model.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".