All-Analog Structures for AF Relaying in mmWave Massive MIMO Systems
Bibliographic record
Abstract
Hybrid analog/digital (A/D) beamforming is preferred in the implementation of relays for mmWave massive multiple-input multiple-output (mMIMO) systems due to the smaller number of radio frequency (RF) chains required compared to fully digital (FD) beamforming. Although the hybrid structure reduces system cost and power consumption, it still requires expensive baseband processing while the unit-modulus constraint in the analog domain limits system performance. In this paper, motivated by these considerations, we propose and investigate the design of all-analog structures for amplify-and-forward (AF) half-duplex relaying in mMIMO systems, which are comprised of the conventional RF components, including: power dividers/combiners, phase-shifters, and delay elements. For the proposed structures, we consider a constrained data rate maximization problem and formulate the AF relay designs. The ensuing solution is not bound to the unit-modulus constraint and does not require RF chains for conversion between analog and baseband domains. Simulation results demonstrate that using the proposed analog structures for AF half-duplex relaying in mMIMO communications can achieve the same performance as the optimal FD relay design.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".