Cooperative relaying in multi-antenna fixed relay networks
Why this work is in the frame
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Bibliographic record
Abstract
Space, cost, and signal processing constraints, among others, often preclude the use of multiple antennas at wireless terminals. This paper investigates distributed decode-and-forward fixed relays (infrastructure-based relaying) which are engaged in cooperation in a two-hop wireless network as a means of removing the burden of multiple antennas on wireless terminals. In contrast to mobile terminals, the deployment of a small number of antennas on infrastructure-based fixed relays is feasible, thus, the paper examines the impact of multiple antennas on the performance of the distributed cooperative fixed relays. Threshold-based maximal ratio combining (MRC) and threshold-based selection combining (SC) of these multiple antenna signals are studied and analyzed. It is found that the end-to-end (E2E) error performance of a network which has few relays with many antennas is not significantly worse than that which has many relays each with a fewer antennas. Obviously, the former network has a tremendous deployment cost advantage over the latter. It is also observed that the E2E error performance of a network in which the multiple antennas at relays are configured in SC fashion is not significantly worse than that in which MRC is used. For implementation, SC presents a significantly lower complexity and cost than a full-blown MRC. The analysis in this paper uses the versatile Nakagami fading channels in contrast to the Rayleigh model used in most previous works
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it