Beamforming in Non-Regenerative MIMO Broadcast Relay Networks
Bibliographic record
Abstract
This paper studies a multiple-input multiple-output (MIMO) broadcast relay channel (BRC), in which a multiple-antenna base station (BS) communicates with multiple-antenna users through an infrastructure-based multiple-antenna relay station (RS). Applying dirty paper coding (DPC) at the BS and linear processing at the RS, our aim is to find the input covariance matrices and the RS beamforming matrix that maximize the system sum-rate. To solve this non-convex problem, a more tractable dual multiple access relay channel (MARC) is investigated and an alternating-minimization algorithm is proposed. Furthermore, the mapping from the resulting covariance matrices for the MARC to the covariance matrices for the BRC is derived. Unlike other existing single-antenna-user schemes, our solution is applicable to a more general network with any number of antennas at the users. Compared with two such single-antenna-user schemes, simulations show that the proposed scheme outperforms the all-pass relay design and performs similarly to the SVD-relay design. Moreover, the proposed design performs close to the sum-rate upper bound with the performance gap decreasing with increasing number of antennas per user. It is also observed that having more antennas at the RS than at the BS is desirable for better system performance.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 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".