Joint transceiver design and user grouping in a MIMO interfering broadcast channel
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Consider a MIMO interfering broadcast channel (multi-cellular network) where each base station transmits signals to the users in its own cell. The basic problem is to design linear transmit/receive beamformers that can maximize the system throughput in the presence of both inter and intra cell interference. To ensure user fairness in the system, we consider the joint user grouping, power allocation and beamformer design problem by maximizing a system utility which aims to strike a suitable trade-off between the user fairness and system throughput. We propose a simple algorithm to solve this nonconcave utility maximization problem and establish its convergence. The simulation results show that the proposed algorithm significantly outperforms the SVD-MMSE method and some other approaches in terms of system throughput while respecting user fairness. The proposed algorithm exhibits fast convergence and is amenable to distributed implementation with limited information exchange.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it