Efficient Group-Sparse Transceiver Design for Multiuser MIMO Relaying in C-RAN
Bibliographic record
Abstract
This paper addresses the design of multiuser MIMO amplify-and-forward relaying within a cloud radio access network (C-RAN) from an energy-efficiency perspective. The aim is to jointly select remote radio heads and optimize their transceiver in order to assist the communication between multiple source-destination pairs. We formulate the design problem as an interference leakage minimization subject to per-relay power constraints along with linear signal preserving constraints at the destinations. To obtain an energy efficient relaying solution, the objective function is penalized with a regularization term which promotes group-sparsity among the resultant relaying weights. A low-complexity iterative algorithm based on the alternating direction method of multipliers (ADMM) is then proposed to solve the regularized problem. Simulation results demonstrate the explicit benefits of the proposed algorithm, which results in notably lower power consumption and computational complexity than conventional relaying design methods.
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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 | 0.000 | 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".