Efficient LTE/Wi-Fi Coexistence in Unlicensed Spectrum Using Virtual Network Entity: Optimization and Performance Analysis
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Bibliographic record
Abstract
Long-term evolution (LTE) operation in the unlicensed spectrum is a promising solution to address the scarcity of licensed spectrum for cellular networks. Although this approach brings higher capacity for LTE networks, the Wi-Fi performance operating in this band can be significantly degraded. To address this issue, we consider a coordinated structure, in which both networks are controlled by a higher level network entity. In such a model, LTE users can transmit in the assigned time-slots, while Wi-Fi users can compete with each other by using p-persistent carrier sense multiple access (CSMA) in their exclusive timeshare. In an unsaturated network, at each duty cycle, the timedivision multiple access (TDMA) scheduling for LTE users and p values for Wi-Fi users should be efficiently updated by the central controller. The corresponding optimization problem is formulated and an iterative algorithm is developed to find the optimal solution using complementary geometric programming and monomial approximations. Aiming to address the qualityof-service assurance for LTE users, an upper bound for average delay of these users is obtained. This analysis could be a basis for the admission control of LTE users in unlicensed bands. The simulation results reveal the performance gains of the proposed algorithm in preserving the Wi-Fi throughput requirement.
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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 | 0.003 |
| Science and technology studies | 0.001 | 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 it