Long Short-Term Memory Based Millimeter Wave Beam Change Prediction via Real-World Data. - Qiaoyu Li; Arumugam Kannan; Himanshu Joshi; Taesang Yoo; Philip Sisk; Mahmoud Taherzadeh Boroujeni; Hamed Pezeshki; Tao Luo 009 (GLOBECOM (Workshops), 2022)

Beyond Codebook-Based Analog Beamforming at mmWave: Compressed Sensing and Machine Learning Methods. - Hamed Pezeshki; Fabio Valerio Massoli; Arash Behboodi; Taesang Yoo; Arumugam Kannan; Mahmoud Taherzadeh Boroujeni; Qiaoyu Li; Tao Luo 009; Joseph B. Soriaga (GLOBECOM, 2022)

Machine Learning Based Time Domain Millimeter-Wave Beam Prediction for 5G-Advanced and Beyond: Design, Analysis, and Over-The-Air Experiments. - Qiaoyu Li; Philip Sisk; Arumugam Kannan; Taesang Yoo; Tao Luo 009; Gaurav Shah; Badri Manjunath; Chanaka Samarathungage; Mahmoud Taherzadeh Boroujeni; Hamed Pezeshki; Himanshu Joshi (IEEE J. Sel. Areas Commun., 2023)

Artificial Intelligence and Machine Learning Based Beam Prediction in 5G-Advanced and 6G Communications. - Qiaoyu Li; Philip Sisk; Arumugam Kannan; Tao Luo 009; Taesang Yoo; Hamed Pezeshki; Mahmoud Taherzadeh Boroujeni (IEEECONF, 2024)