Precoding for MIMO Full-Duplex Amplify-and-Forward Relay Communication Systems
Bibliographic record
Abstract
This paper considers the linear source and relay precoders and destination combiner design for a multiple-input multiple-output (MIMO) full-duplex (FD) amplify-and-forward (AF) relay communication system. The effect of the residual interference due to imperfect loop interference (LI) cancellation is also considered. By taking the full-duplex relay into account, an iterative algorithm is proposed to minimize the mean squared error (MSE) of the received signal at the destination. The original non-convex problem is converted into three convex subproblems, and these are solved alternately to obtain a suboptimal solution to the design problem. The convergence of the iterative algorithm is investigated. Results are presented which show that the proposed FD relay communication system can approximately double the achievable rate compared to the corresponding half-duplex (HD) system when the residual LI level is not high.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".