Cooperative versus Full-Duplex Communication in Cellular Networks: A Comparison of the Total Degrees of Freedom
Bibliographic record
Abstract
In this paper, we compare the potential gain that can be obtained from separate-antenna full-duplex transceivers in cellular networks with that obtained from cooperative operation of half-duplex base stations. The gain is characterized in terms of the total degrees of freedom (DoF). In particular, we consider a system composed of two adjacent MIMO base stations. We consider a single time-frequency resource unit that is used by each base station to communicate with one MIMO user. For the full-duplex case, we assume that each node has a configurable transceiver that can allocate some antennas to the uplink and the remainder to the downlink. We provide an upper bound on the total DoF of the full-duplex system and derive the optimal antenna allocation at each node. We compare the derived upper bound for the full-duplex transceivers with the achievable DoF in the case of half-duplex cooperative multipoint transmission. Our results indicate that the achievable DoF in the cooperative case is always greater than or equal to the upper bound on the DoF of the full-duplex system. We further investigate the case of full-duplex cooperative multipoint transmission and show that the maximum DoF gain due to full-duplex operation cannot exceed 12.5% of the DoF of the half-duplex cooperative system.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".