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Data Driven Environmental Awareness Using Wireless Signals for Efficient Spectrum Sharing
Robust classification of the operational environment of wireless devices is becoming increasingly important for wireless network optimization, particularly in a shared spectrum environment.
SDR-Based 5G NR C-Band I/Q Monitoring and Surveillance in Urban Area Using a Helikite
In this paper, we report experimental results in collectting and processing 5G NR I/Q samples in the 3. 7~GHz C-band by using software-defined radio (SDR)-mounted helikite.
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.
