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Optimizing Unlicensed Coexistence Network Performance Through Data Learning
This work studies NFRs in unlicensed LTE-WiFi (LTE-U and LTE-LAA) networks through supervised learning of network data collected from real-world experiments.
Evolution of Small Cell from 4G to 6G: Past, Present, and Future
To boost the capacity of the cellular system, the operators have started to reuse the same licensed spectrum by deploying 4G LTE small cells (Femto Cells) in the past.
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios
The promise of ML techniques in solving non-linear problems influenced this work which aims to apply known ML techniques and develop new ones for wireless spectrum sharing between Wi-Fi and LTE in the unlicensed spectrum.
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT
This approach delivers an accuracy close to 100% compared to auto-correlation (AC) and energy detection (ED) approaches.
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