Reduced Complexity Rate-Splitting Multiple Access Beamforming for Generalized Objectives
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
Rate splitting multiple access (RSMA) enables interference management trade-offs between space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA) to serve multiple users in the multiple-input multiple-output (MIMO) broadcast channel. The design of RSMA beamforming, or precoding, to maximize typical rate performance is a non-convex optimization problem. In this paper, a parameterization of optimal beamforming directions for different performance maximization problems subject to a total power constraint is obtained for RSMA for systems with full column rank channel matrices. The performance evaluation function may be an arbitrary increasing function of split user rates. The proposed solution combines maximizing each stream’s signal-to-noise-ratio (SNR) and reducing interference on other streams for different objectives. Using the derived beamforming directions, the design is completed by solving a power allocation problem. Simulation results reveal that the proposed approach is able to provide attractive performance/complexity trade-offs compared to existing schemes.
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 | 0.001 | 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