Effect of transmit antenna pattern on RAKE reception in multipath fading channels
Bibliographic record
Abstract
In cellular radio systems, one can take advantage of multi-beam antennas at the cell-site to increase the system capacity and improve the quality of service. The antenna pattern may have an effect on the channel's characteristics in the multipath propagation environments. On the one hand, the use of a sectorized antenna pattern tends to reduce the multipath diversity since a portion of multipath components are suppressed to a certain extent. On the other hand, sometimes the multipath fading can be mitigated for the same reason. This paper investigates the effect of the antenna pattern on the mobile RAKE receiver. We have observed that a higher SNR is required for RAKE reception in a multipath fading environment to guarantee an acceptable bit-error-rate performance and at a given BER, the excess SNR requirements depend on the beamwidth and sidelobe levels of the sectorized antenna, as well as the characteristics of the propagation environment. In a multipath scenario, although the adjacent beams have a relatively high correlation in the channel's impulse response, the RAKE receiver at the mobile can take advantage of the soft-handoff from beam to beam to greatly improve the RAKE reception in fast fading channels. Simulation results are provided.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".