Reduced Complexity Distributed Base Station Processing in the Uplink of Cellular Networks
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Bibliographic record
Abstract
We propose a reduced-complexity belief propagation (RCBP) receiver for joint detection in the uplink of cellular multi-access networks with base station cooperation. Using local message passing algorithms based on belief propagation (BP) has been shown to be very promising for distributed base station processing. Unfortunately, the computational complexity of the BP algorithm grows exponentially with the number of interfering users at each base station. Reducing the computational load of marginalizing the a posteriori probabilities (APP) in BP nodes is challenging because this problem is generally rank deficient, and most well-known sub-optimal detection methods are not efficient in such conditions. In this paper we use an iterative group-wise multiuser detection algorithm to efficiently reduce the complexity of BP receiver. We evaluate the performance and complexity of the proposed RCBP algorithm under decomposed and clustered base station scenarios via simulations.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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