Provisioning Statistical QoS for Coordinated Communications with Limited Feedback
Bibliographic record
Abstract
The capacity performance of ICIC has been extensively studied in coordinated multi-point transmissions (CoMP). In practice however, due to limited feedback, the acquired channel direction information (CDI), which is crucial for ICIC, is often partially available. Hence one may question whether the ICIC is able to meet the Quality-of- Service (QoS) requirements. This paper considers the optimal partitioning of the feedback bits in CoMP while accounting for the inter-cell interference cancellation (ICIC). In this paper, we adopt a statistical model of QoS in CoMP by using the notion of effective capacity (EC). Utilizing EC we then formulate the system function as an optimization problem with the objective of maximizing the total EC subject to the limited feedback available to the cluster of base stations (BSs). Analytical approximations are then obtained on the EC performance which are then utilized as the base for algorithms that assign feedback bits among the user equipments (UEs) and BSs. Using simulations we then investigate the accuracy of the obtained approximations and highlight practical system designs for dealing with stringent delay requirements. Of crucial practical importance, the findings of this paper also indicates that in CoMP there is an optimal cluster size for a given feedback capacity that maximizes the corresponding EC.
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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".