Simulation of Coordinated Multipoint Using Discrete Event Systems Specification
Bibliographic record
Abstract
With the rise in the number of subscribers and to enhance the user experience, Long Term Evolution Advanced (LTE-A) has introduced Coordinated Multipoint (CoMP), a technology which aims to improve the user experience on the cell edge. Although CoMP improves the user experience on the cell edge, it imposes lots of overhead on the network which may result in the degradation of Quality of Service (QoS). To be able to test technologies like CoMP before deploying them on the live network, Modeling and Simulation (M&S) software are required. Through M&S, researchers can test their proposed ideas with minimal costs. Discrete Event System Specification (DEVS) is a formal platform intended for M&S of discrete time systems. In this thesis, we present a dynamic DEVS-based model for simulating CoMP. The model consists of different components that mimic the behavior of entities in LTE-A networks. The model can be used to model different scenarios in both homogenous and Heterogeneous Networks (HetNets). Moreover, we present a new architecture for CoMP developed in collaboration with fellow team members at Carleton University and Ericsson Canada Inc. This new approach reduces the number of control messages in the network, hence, increases download and upload rates. To compare the performance of the newly proposed CoMP architecture with the conventional CoMP architectures, a DEVS-based simulator was developed. The results
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 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".