Multiple-Antenna Multiple-Relay Cooperative Communication System with Beamforming
Bibliographic record
Abstract
In this paper we study the threshold decode and forward (T-DF) fixed relays network with beamforming, which is more reliable than conventional decode and forward (DF) relaying. Deployment of a small number of antennas on fixed relays is easier than on mobile terminals, therefore, the impact of multiple antennas on the outage probability of cooperating fixed relays is considered. Under the total sum power constraint (TSPC) of all relays and also maximum per-relay power constraint (PRPC), the optimum beamforming weights have been found to maximize the received SNR at the destination. It is determined that increasing the number of relays and antennas at each relay increases capacity. The performance of threshold-maximal ratio combining (T-MRC) and threshold-selection combining (T-SC) of the multiple-antenna multiple fixed relays with beamforming is derived. It is observed that the performance of the network with selection combining (SC) configuration is close to the network in which maximal ratio combining (MRC) is used, in addition that it is less complex and less expensive to implement. The outage probability in Rayleigh fading channels is also analyzed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".