Quality of service‐aware coexistence in unlicensed 5G new radio based on time‐domain virtualization
Bibliographic record
Abstract
Summary The deployment of mobile systems is facing several challenges. Precisely, the lack of available licensed bands limits the network capacity, affecting the quality of service (QoS). Consequently, there has been significant interest in utilizing the unlicensed spectrum for mobile data traffic. 3GPP proposed and improved the coexistence of LTE and Wi‐Fi in the unlicensed band starting in Release 13 and the following releases, such as LTE‐LAA and 5G NR‐U. This will cause significant interference and drastically affects the Wi‐Fi users' QoS. To that end, we propose the use of time‐domain virtualization between 5G NR‐U and Wi‐Fi systems. In particular, a scheduling algorithm is proposed, where the sharing mechanism is allocated in time slots rather than allocating a subband frequency for each technology. 5G use cases have different QoS requirements and our proposed solution aims at meeting these requirements. Accordingly, the performance is evaluated by studying the impact of resource virtualization and the coexistence configuration. Simulation results confirm that the minimum rate and maximum delay constraints are met. Moreover, it is shown that resource virtualization improves the throughput in both technologies. Furthermore, the delay performance is displayed for both 5G NR‐U and Wi‐Fi to show any impact of time‐sharing coexistence.
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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 | 0.003 | 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 | 0.003 | 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".