Asynchronous Bidirectional Communication in Cell-Free Networks
Bibliographic record
Abstract
We consider a bidirectional communication between two single-antenna transceivers using multiple multi-antenna access points (APs) in a cell-free network architecture. In such a network, because of different propagation delays associated with different APs, the end-to-end link is a multi-path channel that results in inter-symbol-interference (ISI) in the signals received at the transceivers. To tackle ISI, we resort to cyclic prefix (CP) assisted block transmission of the information symbols and employ joint pre- and post-channel equalizers at both the transceivers to mitigate the impact of intra-block interference. Considering the amplify-and-forward technique at the APs, we cast the joint design of equalizers, beamforming matrices, and transceivers’ transmit powers as a power minimization problem while guaranteeing predefined data rates at the transceivers. Assuming symmetric beamforming matrices at the APs, we devise a semi-closed-form solution for this problem. We prove rigorously that at the optimum only a synchronous subset of the APs should participate in the information exchange between the two transceivers. This is achieved by proving that at the optimum, the pre-equalizer matrices should be unitary and the post-equalizer matrices should be invertible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".