Joint User Grouping and Transceiver Design in a MIMO Interfering Broadcast Channel
Why this work is in the frame
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Bibliographic record
Abstract
Consider a MIMO multi-cellular network (also known as an interfering broadcast channel) where each base station transmits signals to the users in its own cell. The basic problem is to design linear transmit/receive beamformers and schedule users across a fixed set of time slots so as to maximize the system throughput in the presence of both inter and intra cell interference. In this paper, we propose a joint linear transceiver design and user grouping scheme for sum utility maximization that is based on iterative minimization of weighted mean squared error (MSE). The proposed algorithm only needs local channel knowledge and its convergence to a stationary point is guaranteed for some well-known utility functions, while ensuring user fairness. The simulation results show that the proposed formulation/algorithm can offer significantly higher system throughput than the standard multi-user MIMO techniques such as the SVD-MMSE strategy, while maintaining user fairness. Furthermore, the proposed algorithm exhibits fast convergence and is amenable to distributed implementation with limited information exchange.
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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 | 0.000 | 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 | 0.001 |
| 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 it