Multiuser linear precoding for cooperating base stations with asynchronous interference
Bibliographic record
Abstract
This paper addresses multiuser linear precoding using multiple cooperating base stations (BSs). All BSs, and potentially the users, are equipped with multiple antennas. Prior work in multiuser precoding with a single BS extensively uses a downlink/uplink duality that significantly reduces the computation load. Here we show that the presence of asynchronous interference, unfortunately always present due to multiple BSs, precludes a simple duality. This in turn complicates deriving the needed precoding matrices. Even when duality is assumed to exist, asynchronous interference has its implications on the convexity of the power allocation problem. An optimization formulation and several related simulations for the asynchronous case are presented, including one where duality is assumed and another wherein orthogonal frequency division multiplexing (OFDM) is used for transmission and its cyclic prefix is used to mitigate asynchronous reception for edge users.
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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".