Block diagonalization precoding game in a multiuser multicell system
Bibliographic record
Abstract
This paper characterizes the multicell precoding game where block-diagonalization (BD)-based precoding is utilized on a per-cell basis for downlink transmissions. Sharing the same frequency band, the base-station (BS) at each cell wishes to maximize the sum-rate for its connected mobile-stations (MS) with BD precoding. In this context, the paper considers a strategic non-cooperative game (SNG), where each BS greedily determines its precoding strategy in a distributed manner, based on the knowledge of the inter-cell interference (ICI) at its connected MSs. Via the game-theory framework, the existence and uniqueness of a Nash Equilibrium (NE) of this multicell game are subsequently studied. It is shown that there always exists at least one pure NE in the game, whereas the uniqueness of the NE is guaranteed under a certain condition on the ICI. The paper also characterizes the multicell precoding game where BD-Dirty Paper Coding (BD-DPC) is utilized at each BS on a per-cell basis. Simulation results then confirm our analysis on the NE's uniqueness in the BD and BD-DPC multicell precoding games.
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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".