On the design of linear arrays of fixed length for diversity reception in Rayleigh fading and cochannel interference
Bibliographic record
Abstract
The problem of optimizing the placement of the antennas for an optimum combining receiver equipped with a linear antenna array of fixed length is addressed. A Rayleigh fading model is considered where the complex channel gains of both the desired user and the interfering users are assumed to be correlated due to the mutual proximity of the antennas. The average output signal-to-interference-plus-noise ratio is adopted as a measure of the system's performance and is maximized over the number and the arrangement of the antennas in the array. The optimization problem is formulated as a quadratic convex optimization problem in an infinite dimensional space where finite dimensional approximations of the problem are numerically solved using a convex optimization method. For the special case of an exponential correlation function the optimal arrangement is also derived analytically. It is shown for an exponential correlation model that the optimal number of antennas is infinite meaning that adding more antennas is always beneficial. Perhaps unexpectedly, the best arrangement of antennas in this case is not uniform, in general. On the contrary, it is shown through numerical results that for a two dimensional omnidirectional scattering correlation model the optimal number of antennas is a finite number and the optimum placement is uniform.
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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".